Books by Subject
- Advance in structural bioinformatics — Handbook of chemoinformatics algorithms (100)
- Handbook of computational molecular biology — Primer on clinical experience in medicine : reasoning, decision making, and communication in health sciences (100)
- Principles of biomedical informatics. Second edition. [2nd ed.] — Your passport to a career in bioinformatics (43)
- 2015 SpringerDongqing Wei, Qin Xu, Tangzhen Zhao, Hao Dai, editors.This text examines in detail mathematical and physical modeling, computational methods and systems for obtaining and analyzing biological structures, using pioneering research cases as examples. As such, it emphasizes programming and problem-solving skills. It provides information on structure bioinformatics at various levels, with individual chapters covering introductory to advanced aspects, from fundamental methods and guidelines on acquiring and analyzing genomics and proteomics sequences, the structures of protein, DNA and RNA, to the basics of physical simulations and methods for conformation searches. This book will be of immense value to researchers and students in the fields of bioinformatics, computational biology and chemistry. Dr. Dongqing Wei is a Professor at the Department of Bioinformatics and Biostatistics, College of Life Science and Biotechnology, Shanghai Jiaotong University, Shanghai, China. His research interest is in the general area of structural bioinformatics.Also available: Print – 2015
- Advances in mass data analysis of signals and images in medicine, biotechnology, and chemistry : international conferences, MDA 2006/2007, Leipzig, Germany, July 18, 2007 : selected papers2007 SpringerPetra Perner, Ovidio Salvetti (eds.).
- 2007 SpringerPeter Lucas, José A. Gámez, Antonio Salmerón, eds.
- 2008 Springeredited by Roberta Annicchiarico, Ulises Cortés, Cristina Urdiales, editors.
- 2016 Springeredited by Xiangdong Wang, Christian Baumgartner, Denis C. Shields, Hong-Wen Deng, Jacques S Beckmann.The Era of Big Data: From Data-driven Research to Data-driven Clinical Care -- Biostatistics, data mining and computational modeling -- Gene expression and profiling -- The next generation sequencing and applications in clinical research -- Clinical epigenetics and epigenomics -- Proteomic profiling: Data mining and analyses -- Targeted metabolomics: the next generation of clinical chemistry!? -- Clinical bioinformatics for biomarker discovery in targeted metabolomics -- Metagenomic Profiling, Interaction of Genomics with Meta-genomics -- Clinical Epigenetics and Epigenomics -- Integrative Biological Databases -- Standards and Regulations for (Bio)Medical Software -- Clinical applications and systems biomedicine -- Key Law and Policy Considerations for Clinical Bioinformaticians -- Challenges and Opportunities in Clinical Bioinformatics -- Heterogeneity of Hepatocellular Carcinoma.
- 2013 CRCnetBASEGeoff Der, Brian S. Everitt."Adding topics useful to medical statisticians, this new edition of a popular intermediate-level reference explores the use of SAS for analyzing medical data. A new chapter on visualizing data includes a detailed account of graphics for investigating data and smoothing techniques. The book also includes new chapters on measurement in medicine, epidemiology/observational studies, meta-analysis, Bayesian methods, and handling missing data. The book maintains its example-based approach, with SAS code and output included throughout and available online"--Provided by publisher.
- 2008 CRCnetBASEDeyi Li and Yi Du.
- 2008 WHOHealth Metrics Network.This assessment tool describes in detail how to undertake a first baseline assessment of a national HIS. The assessment process is intended to be both catalytic and synergistic. It should move stakeholders towards a shared and broader vision of a more coherent, integrated, efficient and useful system. The gap between the existing system and this new vision will be an important stimulus for moving to the next stage of planning national HIS reform. Such an assessment process can also be a mechanism for directly engaging stakeholders and for reinforcing broad-based consensus-building.--Publisher's description.Also available: Print – 2008
- 2007 CRCnetBASEBrian D. Bissett.
- 2010 CRCnetBASEHojjat Adeli, Samanwoy Ghosh-Dastidar ; in corroboration with Nahid Dadmehr.Time-frequency analysis : wavelet transforms -- Chaos theory -- Classifier designs -- Electroencephalograms and epilepsy -- Analysis of EEGs in an epileptic patient using wavelet transform -- Wavelet-chaos methodology for analysis of EEGs and EEG sub-bands -- Mixed-band wavelet-chaos neural network methodology -- Principal component analysis-enhanced cosine radial basis function neural network -- Alzheimer's disease and models of computation : imaging, classification, and neural models -- Alzheimer's disease : models of computation and analysis of EEGs -- A spatio-temporal wavelet-chaos methodology for EEG-based diagnosis of Alzheimer's disease -- Spiking neural networks : spiking neurons and learning algorithms -- Improved spiking neural networks with application to EEG classification and epilepsy and seizure detection -- A new supervised learning algorithm for multiple spiking neural networks -- Applications of multiple spiking neural networks : EEG classification and epilepsy and seizure detection.
- Bioinformatics-- the impact of accurate quantification on proteomic and genetic analysis and research2014 CRCnetBASEedited by Yu Liu, PhD.
- 2012 Springer Protocolsedited by Richard S. Larson, the University of New Mexio, Albuqerque, NM, USA.Cell perturbation screens for target identification by RNAi / Kubilay Demir and Michael Boutros -- Using functional genomics to identify drug targets : a Dupuytren's disease example / Mirela Sedic, Sandra Kraljevic Pavelic, and Karlo Hock -- Functional characterization of human genes from exon expression and RNA interference results / Dorothea Emig [and others] -- Barcode sequencing for understanding drug-gene interactions / Andrew M. Smith [and others] -- High-throughput sequencing of the methylome using two-base encoding / Christina A. Bormann Chung -- Applications and limitations of in silico models in drug discovery / Ahmet Sacan, Sean Ekins, and Sandhya Kortagere -- Compound Collection Preparation for Virtual screening / Cristian G. Bologa and Tudor I. Oprea -- Mapping between databases of compounds and protein targets / Sorel Muresan, Markus Sitzmann, and Christopher Southan -- Predictive cheminformatics in drug discovery : statistical modeling for analysis of micro-array and gene expression data / N. Sukumar, Michael P. Krein, and Mark J. Embrechts -- Advances in nuclear magnetic resonance for drug discovery / Laurel O. Sillerud and Richard S. Larson -- Human ABC transporter ABCG2 in cancer chemotherapy : drug molecular design to circumvent multidrug resistance / Toshihisa Ishikawa [and others] -- Protein interactions : mapping interactome networks to support drug target discovery and selection / Javier De Las Rivas and Carlos Prieto -- Linking variants from genome-wide association analysis to function via transcriptional network analysis / Benjamin J. Keller, Sebastian Martini, and Viji Nair -- Models of excitation-contraction coupling in cardiac ventricular myocytes / M. Saleet Jafri -- Integration of multiple ubiquitin signals in proteasome regulation / Marta Isasa, Alice Zuin, and Bernat Crosas.
- 2013 Springereditor: Bairong Shen.The book introduces the bioinformatics tools, databases and strategies for the translational research, focuses on the biomarker discovery based on integrative data analysis and systems biological network reconstruction. With the coming of personal genomics era, the biomedical data will be accumulated fast and then it will become reality for the personalized and accurate diagnosis, prognosis and treatment of complex diseases. The book covers both state of the art of bioinformatics methodologies and the examples for the identification of simple or network biomarkers. In addition, bioinformatics software tools and scripts are provided to the practical application in the study of complex diseases. The present state, the future challenges and perspectives were discussed. The book is written for biologists, biomedical informatics scientists and clinicians, etc.
- 2012 SpringerNaiara Rodríguez-Ezpeleta, Michael Hackenberg, Ana M. Aransay, editors.Overview of sequencing technology platforms / Samuel Myllykangas, Jason Buenrostro, and Hanlee P. Ji -- Applications of high-throughput sequencing / Rodrigo Goya, Irmtraud M. Meyer, and Marco A. Marra -- Computational infrastructure and basic data analysis for high-throughput sequencing / David Sexton -- Base-calling for bioinformaticians / Mona A. Sheikh and Yaniv Erlich -- De novo short-read assembly / Douglas W. Bryant Jr. and Todd C. Mockler -- Short-read mapping / Paolo Ribeca -- DNA-protein interaction analysis (ChIP-Seq) / Geetu Tuteja -- Generation and analysis of genome-wide DNA methylation maps / Martin Kerick, Axel Fischer, and Michal-Ruth Schweiger -- Differential expression for RNA sequencing (RNA-Seq) data : mapping, summarization, statistical analysis, and experimental design / Matthew D. Young ... [et al.] -- MicroRNA expression profiling and discovery / Michael Hackenberg -- Dissecting splicing regulatory network by integrative analysis of CLIP-Seq data / Michael Q. Zhang -- Analysis of metagenomics data / Elizabeth M. Glass and Folker Meyer -- High-throughput sequencing data analysis software : current state and future developments / Konrad Paszkiewicz and David J. Studholme.
- 2010 SpringerDarren R. Flower, Matthew N. Davies, Shoba Ranganathan, editors.
- 2011 Springer Protocolsedited by Bernd Mayer.[Publisher-supplied data] Presenting an area of research that intersects with and integrates diverse disciplines, including molecular biology, applied informatics, and statistics, among others, Bioinformatics for Omics Data: Methods and Protocols collects contributions from expert researchers in order to provide practical guidelines to this complex study. Divided into three convenient sections, this detailed volume covers central analysis strategies, standardization and data-management guidelines, and fundamental statistics for analyzing Omics profiles, followed by a section on bioinformatics approaches for specific Omics tracks, spanning genome, transcriptome, proteome, and metabolome levels, as well as an assortment of examples of integrated Omics bioinformatics applications, complemented by case studies on biomarker and target identification in the context of human disease. Written in the highly successful Methods in Molecular Biology series format, chapters contain introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and accessible, Bioinformatics for Omics Data: Methods and Protocols serves as an ideal guide to scientists of all backgrounds and aims to convey the appropriate sense of fascination associated with this research field.
- 2009 Springeredited by Gavin J. Gordon.The emergence of bioinformatics : historical perspective, quick overview and future trends / Christos A. Ouzounis -- The statistical design and interpretation of microarray experiments / Kevin K. Dobbin and Richard M. Simon -- Whole-genome analysis of cancer / Steven A. Enkemann ... [et al.] -- Bioinformatics approaches to the analysis of the transcriptome of animal models of cancer / Mark J. Hoenerhoff ... [et al.] -- Significance of aberrant expression of miRNAs in cancer cells / George A. Calin ... [et al.] -- Proteomic methods in cancer research / Scot Weinberger and Egisto Boschetti -- Comprehensive genomic profiling for biomarker discovery for cancer detection, diagnostics and prognostics / Xiaofeng Zhou ... [et al.] -- Gene expression profiling of the leukemias : oncogenesis, drug responsiveness, and prediction of clinical outcome / Lars Bullinger, Hartmut Dohner, and Jonathon R. Pollack -- Personalized medicine in the clinical management of colorectal cancer / Anthony El-Khoueiry and Heinz Josef Lenz -- PIK3CA gene alterations in human cancers / Sérgia Velho, Carla Oliveira, and Raquel Seruca.
- 2008 NCBI Bookshelfeditors, Arthur Gruber, Alan M. Durham, Chuong Huynh, and Hernado A. del Portillo."This book is intended to serve both as a textbook for short bioinformatics courses and as a base for a self-teaching endeavor. "--Introduction.
- 2006 Springeredited by Nikolay Kolchanov, Ralf Hofestaedt, Luciano Milanesi.
- 2007Jules J. Berman.Status: Not Checked OutLane Catalog Record
- Biomedical informatics : computer applications in health care and biomedicine.. Fourth edition. [4th ed.]2014 SpringerCimino, James J.; Shortliffe, Edward H.Biomedical Informatics: Computer Applications in Health Care and Biomedicine meets the growing demand of practitioners, researchers, educators, and students for a comprehensive introduction to key topics in the field and the underlying scientific issues that sit at the intersection of biomedical science, patient care, public health, and information technology (IT). This 4th edition reflects the remarkable changes in both computing and health care that continue to occur and the exploding interest in the role that IT must play in care coordination and the melding of genomics with innovations in clinical practice and treatment. New chapters have been introduced on the health information infrastructure, consumer health informatics, telemedicine, translational bioinformatics, clinical research informatics, and health IT policy, while the others have all undergone extensive revisions, in many cases with new authors. The organization and philosophy are unchanged, focusing on the science of information and knowledge management and the role of computers and communications in modern biomedical research, health, and health care. Emphasizing the conceptual basis of the field rather than technical details, it provides an introduction and extensive bibliography so that readers can comprehend, assess, and utilize biomedical informatics and health IT. The volume focuses on easy-to-understand examples, a guide to additional literature, chapter summaries, and a comprehensive glossary with concise definitions of recurring terms for self-study or classroom use.
- 2006 SpringerEdward H. Shortliffe, editor; James J. Cimino, associate editor.
- 2014 ProQuest Ebook CentralKevin Bretonnel Cohen, Dina Demner-Fushman.Biomedical Natural Language Processing" is a comprehensive tour through the classic and current work in the field. It discusses all subjects from both a rule-based and a machine learning approach, and also describes each subject from the perspective of both biological science and clinical medicine. The intended audience is readers who already have a background in natural language processing, but a clear introduction makes it accessible to readers from the fields of bioinformatics and computational biology, as well. The book is suitable as a reference, as well as a text for advanced courses in biomedical natural language processing and text mining.
- Biomedical simulation : 4th international symposium, ISBMS 2008, London, UK, July 7-8, 2008 : proceedings2008 SpringerFernando Bello, P.J. "Eddie" Edwards (eds.).
- 2012 Springer Protocolsedited by Luca Monticelli, Emppu Salonen.Ab Initio, density functional theory, and semi-empirical calculations / Mikael P. Johansson, Ville R.I. Kaila, and Dage Sundholm -- Ab Initio molecular dynamics / Kari Laasonen -- Introduction to QM/MM simulations / Gerrit Groenhof -- Computational enzymology / Alessio Lodola and Adrian J. Mulholland -- QM and QM/MM simulations of proteins / Thomas Steinbrecher and Marcus Elstner -- Classical molecular dynamics in a nutshell / Susanna Hug -- Enhanced sampling algorithms / Ayori Mitsutake, Yoshiharu Mori, and Yuko Okamoto -- Force fields for classical molecular dynamics / Luca Monticelli and D. Peter Tieleman -- Polarizable force fields / Hanne S. Antila and Emppu Salonen -- Electrostatics interactions in classical simulations / G. Andres Cisneros, Volodymyr Babin, and Celeste Sagui -- Introduction to best practices in free energy calculations / Michael R. Shirts and David L. Mobley -- Recipes for free energy calculations in biomolecular systems / Mahmoud Moradi [and others] -- Molecular docking methodologies / Andrea Bortolato [and others] -- Simulation studies of the mechanism of membrane transporters / Giray Enkavi [and others] -- Molecular dynamics simulations of lipid bilayers : simple recipe of how to do it / Hector Martinez-Seara and Tomasz Rog -- Simulations of lipid monolayers / Svetlana Baoukina and D. Peter Tieleman -- Simulating DNA by molecular dynamics : aims, methods, and validation / Nicolas Foloppe, Marc Gueroult, and Brigitte Hartmann -- Simulation of carbohydrates, from molecular docking to dynamics in water / Nicolas Sapay, Alessandra Nurisso, and Anne Imberty -- Systematic methods for structurally consistent coarse-grained models / W.G. Noid -- Martini coarse-grained force field / Xavier Periole and Siewert-Jan Marrink -- Multiscale molecular modeling / Matej Praprotnik and Luigi Delle Site -- Coarse-grained models for protein folding and aggregation / Philippe Derreumaux -- Elastic network models : theoretical and empirical foundations / Yves-Henri Sanejouand -- Introduction to dissipative particle dynamics / Zhong-Yuan Lu and Yong-Lei Wang -- Multiscale molecular dynamics simulations of membrane proteins / Syma Khalid and Peter J. Bond -- Vesicles and vesicle fusion : coarse-grained simulations / Julian C. Shillcock.
- 2014 CRCnetBASEJessica Keyes."Where once end users queued up to ask information technology (IT) permission to buy a new computer or new version of software, they are now bypassing IT altogether and buying it on their own. From laptops to smartphones. From iPads to any number of software apps, end users have tasted their freedom and love them. IT is just never going to be the same. Welcome to the brave new world of "bring your own devices" (BYODs). The roots of BYOD can be traced back to the consumerization of all things technology, where technical wizardry is no longer purely the domain of the geek who works for the IT department. Geeks can now be found all over the organization. These workers want to make their own technology choices, whether those choices are on the "approved" list or the company pays for it. Seventy percent of organizations have already adopted BYOD. Gartner predicts this number to increase to 90% by 2014. Most interestingly, a very high percentage of workers think that it is a right rather than a privilege to use their own devices at work. So, it is really not a question of if. It is not even a question of when. It is a question of will you be ready. Of course, the healthcare industry is not the same as most other industries. Hospitals, clinics, and medical offices are not stores, hotels, or assembly lines, although all of these industries are affected by the economy, productivity, regulation, and the need for assessment. hBYOD: Adapting BYOD for the Healthcare Industry provides the guidance necessary for living in this brave new world. You will first learn how to understand these new end users and their demands, as well as the strategic and tactical ramifications of these demands. BYOD will then cover the broad range of technical considerations such as selection, "-- Provided by publisher.
- 2007 Springeredited by Igor Jurisica, Dennis A. Wigle, Bill Wong.Also available: Print – 2007
- 2011 SpringerKeith W. Boone.Organization of This Book -- Clinical Documentation -- The HL7 Clinical Document Architecture -- Extensible Markup Language -- Basic Data Types -- Text and Multimedia -- Demographic Data -- Codes and Vocabularies -- Codes -- Dates and Times -- Collections -- HL7 Version 3 Modeling -- Clinical Document Infrastructure -- The CDAtm Header -- The CDAtm Body -- Clinical Statements in the CDAtm -- HL7 Version 2 to CDAtm Release 2 -- Extracting Data from a CDAtm Document -- Templates -- Validating the Content of a CDAtm Document -- Implementation Guides on CDAtm.
- 2011 Springer Protocolsedited by Joe Zhongxiang Zhou.Historical overview of chemical library design / Roland E. Dolle -- Chemoinformatics and library design / Joe Zongxiang Zhou -- Molecular library design using multi-objective optimization methods / Christos A. Nicolaou and Christos C. Kannas -- A scalable approach to combinatorial library design / Puneet Sharma, Srinivasa Salapaka, and Carolyn Beck -- Application of Free-Wilson selectivity analysis for combinatorial library design / Simone Sciabola ... [et al.] -- Application of QSAR and shape pharmacophore modeling approaches for targeted chemical library design / Jerry O. Ebalunode, Weifan Zheng, and Alexander Tropsha -- Combinatorial library design from reagent pharmacophore fingerprints / Hongming Chen, Ola Engkvist, and Niklas Blomberg -- Docking methods for structure-based library design / Claudio N. Cavasotto and Sharangdhar S. Phatak -- Structure-based library design in efficient discovery of novel inhibitors / Shunqi Yan and Robert Selliah -- Structure-based and property-compliant library design of 11[beta]-HSD1 adamantyl amide inhibitors / Genevieve D. Paderes ... [et al.] -- Design of screening collections for successful fragment-based lead discovery / James Na and Qiyue Hu -- Fragment-based drug design / Eric Feyfant ... [et al.] -- LEAP into the Pfizer Global Virtual Library (PGVL) space : creation of readily synthesizable design ideas automatically / Qiyue Hu ... [et al.] -- The design, annotation, and application of a kinase-targeted library / Hualin Xi and Elizabeth A. Lunney -- PGVL hub : an integrated desktop tool for medicinal chemists to streamline design and synthesis of chemical libraries and singleton compounds / Zhengwei Peng ... [et al.] -- Design of targeted libraries against the human Chk1 kinase using PGVL hub / Xengwei Peng and Qiyue Hu -- GLARE : a tool for product-oriented design of combinatorial libraries / Jean-François Truchon -- CLEVER : a general design tool for combinatorial libraries / Tze Hau Lam ... [et al.].
- 2010 Springer Protocolsedited by Jürgen Bajorath.Some Trends in Chem(o)informatics / Wendy A. Warr -- Molecular Similarity Measures / Gerald M. Maggiora and Veerabahu Shanmugasundaram -- The Ups and Downs of Structure-Activity Landscapes / Rajarshi Guha -- Computational Analysis of Activity and Selectivity Cliffs / Lisa Peltason and Jurgen Bajorath -- Similarity Searching Using 2D Structural Fingerprints / Peter Willett -- Predicting the Performance of Fingerprint Similarity Searching / Martin Vogt and Jurgen Bajorath -- Bayesian Methods in Virtual Screening and Chemical Biology / Andreas Bender -- Reduced Graphs and Their Applications in Chemoinformatics / Kristian Birchall and Valerie J. Gillet -- Fragment Descriptors in Structure-Property Modeling and Virtual Screening / Alexandre Varnek -- The Scaffold Tree: An Efficient Navigation in the Scaffold Universe / Peter Ertl, Ansgar Schuffenhauer, and Steffen Renner -- Pharmacophore-Based Virtual Screening / Dragos Horvath -- De Novo Drug Design / Markus Hartenfeller and Gisbert Schneider -- Classification of Chemical Reactions and Chemoinformatics Processing of Enzymatic Transformations / Diogo A.R.S. Latino and Joao Aires-de-Sousa -- Informatics Approach to the Rational Design of siRNA Libraries / Jerry O. Ebalunode, Charles Jagun, and Weifan Zheng -- Beyond Rhodopsin: G Protein-Coupled Receptor Structure and Modeling Incorporating the b2-adrenergic and Adenosine A2A Crystal Structures / Andrew J. Tebben and Dora M. Schnur -- Methods for Combinatorial and Parallel Library Design / Dora M. Schnur, Brett R. Beno, Andrew J. Tebben, and Cullen Cavallaro -- The Interweaving of Cheminformatics and HTS / Anne Kummel and Christian N. Parker -- Computational Systems Chemical Biology / Tudor I. Oprea, Elebeoba E. May, Andrei Leitao, and Alexander Tropsha -- Ligand-Based Approaches to In Silico Pharmacology / David Vidal, Ricard Garcia-Serna, and Jordi Mestres -- Molecular Test Systems for Computational Selectivity Studies and Systematic Analysis of Compound Selectivity Profiles / Dagmar Stumpfe, Eugen Lounkine, and Jurgen Bajorath -- Application of Support Vector Machine-Based Ranking Strategies to Search for Target-Selective Compounds / Anne Mai Wassermann, Hanna Geppert, and Jurgen Bajorath -- What Do We Know?: Simple Statistical Techniques that Help / Anthony Nicholls.
- 2014 Wileyedited by Jürgen Bajorath.
- 2014 Springer Protocolsedited by Ronald J.A. Trent.From the phenotype to the genotype via bioinformatics / Cali E. Willet and Claire M. Wade -- Production and analytic bioinformatics for next-generation DNA sequencing / Richard James Nigel Allcock -- Analyzing the metabolome / Francis G. Bowling and Mervyn Thomas -- Statistical perspectives for genome-wide association studies (GWAS) / Jennifer H. Barrett, John C. Taylor, and Mark M. Iles -- Bioinformatics challenges in genome-wide association studies (GWAS) / Rishika De, William S. Bush, and Jason H. Moore -- Studying cancer genomics through next-generation DNA sequencing and bioinformatics / Maria A. Doyle [and others] -- Using bioinformatics tools to study the role of microRNA in cancer / Fabio Passetti [and others] -- Chromosome microarrays in diagnostic testing : interpreting the genomic data / Greg B. Peters and Mark D. Pertile -- Bioinformatics approach to understanding interacting pathways in neuropsychiatric disorders / Ali Alawieh [and others] -- Pathogen genome bioinformatics / Vitali Sintchenko and Michael P.V. Roper -- Setting up next-generation sequencing in the medical laboratory / Bing Yu -- Managing incidental findings in exome sequencing for research / Marcus J. Hinchcliffe -- Approaches for classifying DNA variants found by sanger sequencing in a medical genetics laboratory / Pak Leng Cheong and Melody Caramins -- Designing algorithms for determining significance of DNA missense changes / Sivakumar Gowrisankar and Matthew S. Lebo -- DNA variant databases : current state and future directions / John-Paul Plazzer and Finlay Macrae -- Natural language processing in biomedicine : a unified system architecture overview / Son Doan [and others] -- Candidate gene discovery and prioritization in rare diseases / Anil G. Jegga -- Computer-aided drug designing / Mohini Gore and Neetin S. Desai.
- 2008 Springer Protocolsedited by Ronald J.A. Trent.In silico gene discovery / Bing Yu -- Whole genome-wide association study using Affymetrix SNP chip : a two-stage sequential selection method to identify genes that increase the risk of developing complex diseases / Howard H. Yang ... [et al.] -- Utilizing HapMap and tagging SNPs / Christopher A. Haiman and Daniel O. Stram -- Measuring the effects of genes and environment on complex traits / Jennifer H. Barrett -- Microarrays-planning your experiment / Jean Yee Hwa Yang -- Clinical uses of microarrays in cancer research / Carl Virtanen and James Woodgett -- Microarrays-analysis of signaling pathways / Anassuya Ramachandran ... [et al.] -- Microarrays-identifying molecular portraits for prostate tumors with different Gleason patterns / Alexandre Mendes, Rodney J. Scott, and Pablo Moscato -- Microarrays for the study of viral gene expression during human cytomegalovirus latent infection / Barry Slobedman and Allen K.L. Cheung -- Computer-assisted reading of DNA sequences / Huong Le ... [et al.] -- Evaluating DNA sequence variants of unknown biological significance / Scott A. Grist, Andrew Dubowsky, and Graeme Suthers -- Developing a DNA variant database / David C.Y. Fung -- Protein comparative sequence analysis and computer modeling / Brett D. Hambly, Cecily E. Oakley, and Piotr G. Fajer -- Identification and characterization of microbial proteins using peptide mass fingerprinting strategies / Jonathan W. Arthur -- Statistical analysis of image data provided by two-dimensional gel electrophoresis for discovery proteomics / Ben Crossett ... [et al.] -- Online resources for the molecular contextualization of disease / Chi N.I. Pang and Marc R. Wilkins -- Web-based resources for clinical bioinformatics / Anthony M. Joshua and Paul C. Boutros -- Developing decision support systems in clinical bioinformatics / Vitali Sintchenko and Enrico Coiera -- eConsulting / Siaw-Teng Liaw and Peter Schattner.
- 2007 ScienceDirectedited by Robert A. Greenes.This book examines the nature of medical knowledge, how it is obtained, and how it can be used for decision support. It provides complete coverage of computational approaches to clinical decision-making. Chapters discuss data integration into healthcare information systems and delivery to point of care for providers, as well as facilitation of direct to consumer access. A case study section highlights critical lessons learned, while another portion of the work examines biostatistical methods including data mining, predictive modelling, and analysis. This book additionally addresses organizational, technical, and business challenges in order to successfully implement a computer-aided decision-making support system in healthcare delivery.
- 2014 ScienceDirect2014 ClinicalKeyedited by Robert A. Greenes.Sect. 1: Computer-based clinical decision support: overview, status, and challenges. Ch. 1. Definition, scope and challenges / Robert A. Greenes -- Ch. 2. A brief history of clinical decision support / Robert A. Greenes -- Ch. 3. Features of computer-based clinical decision support / Robert A. Greenes -- Ch. 4. The role of quality measurement and reporting feedback as a driver for care improvement / Floyd Eisenberg -- Sect. 2: Experience with CDS development and adoption : case studies, national initiatives, and lessons learned. Ch. 5. Regenstrief medical informatics / Paul Biondich, [et al.] -- Ch. 6. Patients, doctors, and information technology : clinical decision support at Brigham and Women's Hospital and Partners HealthCare / Adam Wright and David W. Bates -- Ch. 7. Computer-based approaches to improving healthcare quality and safety at LDS Hospital / R. Scott Evans -- Ch. 8. International dimensions of clinical decision support / Hamish Fraser and Jeremy Wyatt -- Ch. 9. Current state of CDS utilization / Robert A. Greenes -- Sect. 3: Sources of knowledge for clinical decision support. Ch. 10. Human-intensive techniques / Vimla L. Patel and Edward H. Shortliffe -- Ch. 11. Generation of knowledge for clinical decision support / Michael E. Matheny and Lucila Ohno-Machado -- Ch. 12. Modernizing evidence synthesis for evidence-based medicine / Byron C. Wallace, [et al.] -- Ch. 13. Big data and population-based decision support / Michael A. Krall, Adi V. Gundlapalli and Matthew H. Samore -- Ch. 14. Clinical decision support for personalized medicine / Brandon M. Welch, [et al.]. Sect. 4: The technology of clinical decision support. Ch. 15. Decision rules and expressions / Robert A. Jenders -- Ch. 16. Guidelines and workflow models / Mor Peleg and Arturo González-Ferrer -- Ch. 17. Ontologies, vocabularies and data models / Stanley M. Huff, [et al.] -- Ch. 18. Grouped knowledge elements / Margarita Sordo and Aziz A. Boxwala -- Ch. 19. Infobuttons and point of care access to knowledge / Guilherme Del Fiol, Hong Yu and James J. Cimino -- Ch. 20. Formal representations and semantice web technologies / Alan Rector and Davide Sottara -- Ch. 21. The role of standards / Kensaku Kawamoto and Robert A. Greenes -- Sect. 5: Adoption of clinical decision support. Ch. 22. Cognitive considerations for health information technology / Amy Franklin and Jiajie Zhang -- Ch. 23. Organizational and cultural change / Joan S. Ash and Timothy H. Hartzog -- Ch. 24. Managing the investment in clinical decision support / John Glaser and Tonya Hongsermeier -- Ch. 25. A clinical decision support implementation guide : practical considerations / Donald Levick and Jerome Osheroff -- Ch. 26. Legal and regulatory issues related to the use of clinical software in health care delivery / Steven H. Brown and Randolph A. Miller -- Ch. 27. Consumers and clinical decision support / Nananda Col and Rosaly Correa-de-Araujo -- Sect. 6: The journey to widespread use of clinical decision support. Ch. 28. A clinical knowledge management program / Roberto A. Rocha, [et al.] -- Ch. 29. Integration of knowledge resources into applications to enable CDS / Kensaku Kawamoto, Emory Fry and Robert Greenes -- Ch. 30. Looking ahead : the road to broad adoption / Robert A. Greenes.
- 2007 SpringerEta S. Berner, editor.Overview of clinical decision support systems / Eta S. Berner and Tonya J. La Londe -- Mathematical foundations of decision support systems / S. Andrew Spooner -- Data mining and clinical decision support systems / J. Michael Hardin and David C. Chhieng -- Design and implementation issues / Jerome H. Carter -- Diagnostic decision support systems / Randolph A. Miller and Antoine Geissbuhler -- Ethical and legal issues in decision support / Kenneth W. Goodman -- Clinical trials of information interventions / E. Andrew Balas and Suzanne Austin Boren -- Clinical decision support at Intermountain Healthcare / Peter J. Haug ... [et al.] -- Clinical decision support within the Regenstrief medical record system / Burke W. Mamlin ... [et al.] -- Decision support during inpatient care provider order entry : the Vanderbilt experience / Randolph A. Miller ... [et al.] -- Decision support for patients / Holly B. Jimison, Paul P. Sher, Jennifer J.B. Jimison.
- 2016 SpringerJohn T. Finnell, Brian E. Dixon, editors.This study guide is written to support the formal training required to become certified in clinical informatics. The content is structured to define and introduce key concepts with examples drawn from real-world experiences in order to impress upon the reader the core content from the field of clinical informatics. The book is divided into sections that group related chapters based on the major foci of the core content: health care delivery; clinical decision-making; information systems; leadership and managing teams; and professionalism. The chapters do not need to be read or taught in order, although the suggested order is consistent with how the editors have structured their curricula over the years. Clinical Informatics Study Guide: Text and Review serves as a reference for those seeking to independently study for a certifying examination or periodically reference while in practice. It further provides a roadmap for faculty who wish to go deeper in courses designed for physician fellows or graduate students in a variety of clinically oriented informatics disciplines, such as nursing, pharmacy, radiology, and public health.
- 2014 CambridgeCecily Morrison, Matthew R. Jones, Julie Bracken."This book discusses the issues that need to be considered when selecting and implementing a CIS in critical care. Common mistakes and pitfalls are highlighted. When appropriate, it offers evidence from research in health informatics and organisational change. This book is for all those involved in the selection, purchase, implementation, and use of a CIS. This includes clinicians, nurses, allied healthcare professional, managers, and executives. It is a key in the success of a CIS implementation project to include as many stakeholders as possible. This book can inform and support discussion between multiple stakeholders"--Provided by publisher.
- 2012 SpringerRachel L. Richesson, James E. Andrews, editors."This book provides foundational coverage of key areas, concepts, constructs, and approaches of medical informatics as it applies to clinical research activities, in both current settings and in light of emerging policies. The field of clinical research is fully characterized (in terms of study design and overarching business processes), and there is emphasis on information management aspects and informatics implications (including needed activities) within various clinical research environments. The purpose of the book is to provide an overview of clinical research (types), activities, and areas where informatics and IT could fit into various activities and business practices. This book introduces and applies informatics concepts only as they have particular relevance to clinical research settings"--Provided by publisher.
- 2011 CRCnetBASEA.K. Soman.1. What are cloud services? -- 2. Benefits and drawbacks of cloud services -- 3. Cloud technologies -- 4. Cloud-based solutions for healthcare IT -- 5. HIPAA and HITECH : cloud perspective -- 6. Adopting cloud services -- 7. Interoperability -- 8. Cloud-based personal health records (PHR) -- 9. Case studies.
- 2015 SpringerVimla L. Patel, Thomas G. Kannampallil, David R. Kaufman, editors.
- Cognitive informatics in health and biomedicine : case studies on critical care, complexity and errors2014 SpringerVimla L. Patel, David R. Kaufman, Trevor Cohen, editors."Enormous advances in information technology have permeated essentially all facets of life in the past two decades. Formidable challenges remain in fostering tools that enhance productivity but are sensitive to work practices. Cognitive Informatics (CI) is the multidisciplinary study of cognition, information and computational sciences that investigates all facets of human computing including design and computer-mediated intelligent action, thus is strongly grounded in methods and theories from cognitive science. As an applied discipline, it has a close affiliation with human factors and human-computer interaction, and provides a framework for the analysis and modeling of complex human performance in technology-mediated settings and contributes to the design and development of better information systems. In recent years, CI has emerged as a distinct area with special relevance to biomedicine and health care. In addition, it has become a foundation for education and training of health informaticians, the Office of the National Coordinator for Health Information Technology initiating a program including CI as one of its critical elements to support health IT curriculum development. This book represents a first textbook on cognitive informatics and will focus on key examples drawn from the application of methods and theories from CI to challenges pertaining to the practice of critical-care medicine (CCM). Technology is transforming critical care workflows and re-organizing patient care management processes. CCM has proven to be a fertile test bed for theories and methods of cognitive informatics. CI, in turn, has contributed much to our understanding of the factors that result in complexity and patient errors. The topic is strongly interdisciplinary and will be important for individuals from a range of academic and professional backgrounds, including critical care specialists, psychologists, computer scientists, medical informaticians, and anthropologists"--Provided by publisher.
- 2013 SpringerAdam I. Levine, Samuel DeMaria Jr., Andrew D. Schwartz, Alan J. Sim, editors.Part I. Introduction to simulation -- Part II. Simulation modalities and technologies -- Part III. Simulation for healthcare disciplines -- Part IV. Professional development in simulation -- Part V. Program development in simulation -- Appendices -- Index.
- 2006 Springeredited by Wei Zhang and Ilya Shmulevich.
- 2015 SpringerAndrew E. Teschendorff, editor.This book introduces the reader to modern computational and statistical tools for translational epigenomics research. Over the last decade, epigenomics has emerged as a key area of molecular biology, epidemiology and genome medicine. Epigenomics not only offers us a deeper understanding of fundamental cellular biology, but also provides us with the basis for an improved understanding and management of complex diseases. From novel biomarkers for risk prediction, early detection, diagnosis and prognosis of common diseases, to novel therapeutic strategies, epigenomics is set to play a key role in the personalized medicine of the future. In this book we introduce the reader to some of the most important computational and statistical methods for analyzing epigenomic data, with a special focus on DNA methylation. Topics include normalization, correction for cellular heterogeneity, batch effects, clustering, supervised analysis and integrative methods for systems epigenomics. This book will be of interest to students and researchers in bioinformatics, biostatistics, biologists and clinicians alike. Dr. Andrew E. Teschendorff is Head of the Computational Systems Genomics Lab at the CAS-MPG Partner Institute for Computational Biology, Shanghai, China, as well as an Honorary Research Fellow at the UCL Cancer Institute, University College London, UK.
- Computational biology : a practical introduction to biodata processing and analysis with Linux, MySQL, and R. 2nd ed.2013 SpringerRöbbe Wünschiers.This greatly expanded 2nd edition provides a practical introduction to - data processing with Linux tools and the programming languages AWK and Perl- data management with the relational database system MySQL, and- data analysis and visualization with the statistical computing environment R for students and practitioners in the life sciences. Although written for beginners, experienced researchers in areas involving bioinformatics and computational biology may benefit from numerous tips and tricks that help to process, filter and format large datasets. Learning by doing is the basic concept of this book. Worked examples illustrate how to employ data processing and analysis techniques, e.g. for - finding proteins potentially causing pathogenicity in bacteria, - supporting the significance of BLAST with homology modeling, or- detecting candidate proteins that may be redox-regulated, on the basis of their structure. All the software tools and datasets used are freely available. One section is devoted to explaining setup and maintenance of Linux as an operating system independent virtual machine. The author's experiences and knowledge gained from working and teaching in both academia and industry constitute the foundation for this practical approach.
- 2011 AtyponOzkan Ufuk Nalbantoglu and Khalid Sayood.Recent advances in development of sequencing technology has resulted in a deluge of genomic data. In order to make sense of this data, there is an urgent need for algorithms for data processing and quantitative reasoning. An emerging in silico approach, called computational genomic signatures, addresses this need by representing global species-specific features of genomes using simple mathematical models. This text introduces the general concept of computational genomic signatures, and it reviews some of the DNA sequence models which can be used as computational genomic signatures. The text takes the position that a practical computational genomic signature consists of both a model and a measure for computing the distance or similarity between models. Therefore, a discussion of sequence similarity/distance measurement in the context of computational genomic signatures is presented. The remainder of the text covers various applications of computational genomic signatures in the areas of metagenomics, phylogenetics and the detection of horizontal gene transfer.
- 2012 SpringerZlatko Trajanoski, editor.Bioinformatic Tools for the Search of Disease-Associated Variations / Stefan Coassin, Anita Kloss-Brandstätter and Florian Kronenberg -- Cloud Computing / Bringing Computational Power to Medical Genetics / Lukas Forer, Sebastian Schönherr, Hansi Wei€ensteiner, Günther Specht and Florian Kronenberg, et al. -- High-Throughput Characterization and Comparison of Microbial Communities / Bettina Halwachs, Gregor Gorkiewicz and Gerhard G. Thallinger -- Microarray Meta-Analysis: From Data to Expression to Biological Relationships / Julia Feichtinger, Gerhard G. Thallinger, Ramsay J. McFarlane and Lee D. Larcombe -- Analysis of Labeled Quantitative Mass Spectrometry Proteomics Data / Florian Paul Breitwieser and Jacques Colinge -- Lipidomics, Mass Spectrometry, and Bioinformatics / Jürgen Hartler, Harald C. Köfeler, Christopher J. O. Baker, Ravi Tharakan and Gerhard G. Thallinger -- Protein Sequence-Structure-Function-Network Links Discovered with the ANNOTATOR Software Suite: Application to ELYS/Mel-28 / Georg Schneider, Westley Sherman, Durga Kuchibhatla, Hong Sain Ooi and Fernanda L. Sirota, et al. -- 3D Structure and Drug Design / Kristina Djinović-Carugo and Oliviero Carugo -- Integrating Biomolecular and Clinical Data for Cancer Research: Concepts and Challenges / Pornpimol Charoentong, Hubert Hackl, Bernhard Mlecnik, Gabriela Bindea and Jerome Galon, et al. -- Applied Data Mining: From Biomarker Discovery to Decision Support Systems / M. Osl, M. Netzer, S. Dreiseitl and C. Baumgartner -- Network-Based Methods for Computational Diagnostics by Means of R / Laurin A. J. Mueller, Matthias Dehmer and Frank Emmert-Streib.
- 2017 Wileyedited by Matthias Dehmer, Yongtang Shi, and Frank Emmert-Streib.Using the DiffCorr Package to Analyze and Visualize Differential Correlations in Biological Networks / Atsushi Fukushima, Kozo Nishida -- Analytical Models and Methods for Anomaly Detection in Dynamic, Attributed Graphs / Benjamin A Miller, Nicholas Arcolano, Stephen Kelley, Nadya T Bliss -- Bayesian Computational Algorithms for Social Network Analysis / Alberto Caimo, Isabella Gollini -- Threshold Degradation in R Using iDEMO / Chien-Yu Peng, Ya-Shan Cheng -- Optimization of Stratified Sampling with the R Package SamplingStrata: Applications to Network Data / Marco Ballin, Giulio Barcaroli -- Exploring the Role of Small Molecules in Biological Systems Using Network Approaches / Rajarshi Guha, Sourav Das -- Performing Network Alignments with R / Qiang Huang, Ling-Yun Wu -- l1-Penalized Methods in High-Dimensional Gaussian Markov Random Fields / Luigi Augugliaro, Angelo M Mineo, Ernst C Wit -- Cluster Analysis of Social Networks Using R / Malika Charrad -- Inference and Analysis of Gene Regulatory Networks in R / Ricardo de M Simoes, Matthias Dehmer, Constantine Mitsiades, Frank Emmert-Streib -- Visualization of Biological Networks Using NetBioV / Shailesh Tripathi, Salissou Moutari, Matthias Dehmer, Frank Emmert-Streib.
- 2007 ScienceDirectedited by Paul Cisek, Trevor Drew, John F. Kalaska.
- 2014 ScienceDirectedited by Roland Eils, Andres Kriete.Introducing computational systems biology / Roland Eils, Andres Kriete -- Structural systems biology : modeling interactions and networks for systems studies / Robert B. Russell, Gordana Apic, Olga Kalinina, Leonardo Trabuco, Matthew J. Betts, Qianhao Lu -- Understanding principles of the dynamic biochemical networks of life through systems biology / Hans V. Westerhoff, Fei He, Ettore Murabito, Frederic Cremazy, Matteo Barberis -- Biological foundations of signal transduction, systems biology and aberrations in disease / Ursula Klingmuller, Marcel Schilling, Sofia Depner, Lorenza A. D'Alessandro -- Complexities in quantitative systems analysis of signaling networks / Christina Kiel, Luis Serrano -- Gene networks : estimation, modeling, and simulation / Seiya Imoto, Hiroshi Matsuno, Satoru Miyano -- Reconstruction of metabolic network from genome information and its structural and functional analysis / Hong-Wu Ma, An-Ping Zeng -- Standards, platforms, and applications / Stanley Gu, Herbert Sauro -- Databases, standards, and modeling platforms for systems biology / Juergen Eils, Elena Herzog, Baerbel Felder, Christian Lawerenz, Roland Eils -- Computational models for circadian rhythms : deterministic versus stochastic approaches / Jean-christophe Leloup, Didier Gonze, Albert Goldbeter -- Top-down dynamical modeling of molecular regulatory networks / Reinhard Laubenbacher, Pedro Mendes -- Discrete gene network models for understanding multicellularity and cell reprogramming : from network structure to attractor landscapes landscape / Joseph Xu Zhou, Xiaojie Qiu, Aymeric Fouquier D'Herouel, Sui Huang -- Stochastic simulations of cellular processes : from single cells to colonies / John Cole, Mike J. Hallock, Piyush Labhsetwar, Joseph R. Peterson, John E. Stone, Zaida Luthey-Schulten -- Advances in machine learning for processing and comparison of metagenomic data / Jean-Luc Bouchot, William L. Trimble, Gregory Ditzler, Yemin Lan, Steve Essinger, Gail Rosen -- Systems biology of infectious diseases and vaccines / Helder I. Nakaya -- From cell behavior to tissue deformation : computational modeling and simulation of early animal embryogenesis with the mecagen platform / Julien Delile, Ren Doursat, Nadine Peyriras -- Developing a systems biology of aging / Andres Kriete, Mathieu Cloutier -- Morphometric analysis of tissue heterogeneity in glioblastoma multiforme -- Applications in cancer research : mathematical models of apoptosis / Stefan M. Kallenberger, Stefan Legewie, Roland Eils.
- 2012 SpringerNicolas Le Novère, editors.Functional Genomics and Molecular Networks Gene Expression Regulations in Complex Diseases: Down Syndrome as a Case Study / Marie-Claude Potier and Isabelle Rivals -- Reconstructing Models from Proteomics Data / Lysimachos Zografos, Andrew J. Pocklington and J. Douglas Armstrong -- Using Chemical Kinetics to Model Neuronal Signalling Pathways / Lukas Endler, Melanie I. Stefan, Stuart J. Edelstein and Nicolas Le Novère -- Breakdown of Mass-Action Laws in Biochemical Computation / Fidel Santamaria, Gabriela Antunes and Erik De Schutter -- Spatial Organization and Diffusion in Neuronal Signaling / Sherry-Ann Brown, Raquell M. Holmes and Leslie M. Loew -- The Performance (and Limits) of Simple Neuron Models: Generalizations of the Leaky Integrate-and-Fire Model / Richard Naud and Wulfram Gerstner -- Multi-compartmental Models of Neurons / Upinder S. Bhalla -- Noise in Neurons and Other Constraints / A. Aldo Faisal -- Methodological Issues in Modelling at Multiple Levels of Description / Kevin Gurney and Mark Humphries -- Virtues, Pitfalls, and Methodology of Neuronal Network Modeling and Simulations on Supercomputers / Anders Lansner and Markus Diesmann -- Co-operative Populations of Neurons: Mean Field Models of Mesoscopic Brain Activity / David T. J. Liley, Brett L. Foster and Ingo Bojak -- Cellular Spacing: Analysis and Modelling of Retinal Mosaics / Stephen J. Eglen -- Measuring and Modeling Morphology: How Dendrites Take Shape / Todd A. Gillette and Giorgio A. Ascoli -- Axonal Growth and Targeting / Duncan Mortimer, Hugh D. Simpson and Geoffrey J. Goodhill -- Encoding Neuronal Models in SBML / Sarah M. Keating and Nicolas Le Novère -- NeuroML / Padraig Gleeson, Volker Steuber, R. Angus Silver and Sharon Crook -- XPPAUT / Bard Ermentrout -- NEST by Example: An Introduction to the Neural Simulation Tool NEST / Marc-Oliver Gewaltig, Abigail Morrison and Hans Ekkehard Plesser.
- 2013 ScienceDirectedited by Bruce A. Fowler.Computational Toxicology: Methods and Applications for Risk Assessment is an essential reference on the translation of computational toxicology data into information that can be used for more informed risk assessment decision-making. This book is authored by leading international investigators who have real-world experience in relating computational toxicology methods to risk assessment. Key topics of interest include QSAR modeling, chemical mixtures, applications to metabolomic and metabonomic data sets, toxicogenomic analyses, applications to REACH informational strategies and much more. With a free companion website featuring an image bank from the book and web links for further research and reading, this authoritative reference is your complete guide to computational toxicology methods and applications to risk assessment. Authored by leading international researchers engaged in cutting-edge applications of computational methods for translating complex toxicological data sets into useful risk assessment information. Incorporates real-world examples of how computational toxicological methods have been applied to advance the science of risk assessment Provides the framework necessary for new technologies and fosters common vocabularies and principles upon which the effects of new chemical entities should be compared.
- Computational vision and medical image processing : Vipimage 2011 : proceedings of VIPIMAGE 2011, Third ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing, Olhão, Algarve, Portugal, 12-14 October 20112012 CRCnetBASEeditors, João Manuel R.S. Tavares and R.M. Natal Jorge.
- 2008 ProQuest Ebook Centraledited by Annette ten Teije, Silvia Miksch and Peter Lucas.Part I.A Primer -- 1. Guideline development -- 2. Computer-interpretable guideline formalisms -- 3. Form guidelines and careflows: modeling and supporting complex clinical processes -- 4. Formal methods for verification of clinical practice guidelines -- 5. The Temporal aspects of clinical guidelines -- 6. Planning: supporting and optimizing clinical guidelines optimization -- 7. Adaptation of clinical practice guidelines -- 8. Visualization methods to support guideline-based care management -- 9. Compliance with clinical practice guidelines -- -- Part II. Current Trends -- Compliance checking of cancer-screening careflows: an approach based on computational logic -- Medical guidelines for the patient: introducing the life assistance protocols -- DeGeL: a clinical-guidelines library and automated guideline-support tools -- A Constraint-based approach to medical guidelines and protocols -- TSNet: a distributed architecture for time series analysis -- Clinical guidelines and care pathways: a case study applying PROforma decision support technology to the breast cancer care pathway -- Lessons learned from adapting a generic narrative diabetic-foot guideline to an institutional decision-support system -- Verification of medical guidelines of in KIV -- Improving the execution of clinical guidelines and temporal data abstraction in high-frequency domains -- Appling artificial intelligence to clinical guidelines: the GLARE approach.
- 2012 SpringerMorris F. Collen.
- 2006 ProQuest Ebook Centraledited by Hyeoun-Ae Park, Peter Murray, and Connie Delaney.
- 2016 SpringerThomas Wetter ; with contributions by George Demiris, Amanda K. Hall, Andrea Hartzler, Jina Huh, Georgios Raptis and Lisa M. Vizer.Part I. Introducing the Domain and Levels of Service -- 1. Character of domain and organization of book -- 2. Economy 1: immanent mismatch between demand and supply of health care workforce -- 3. Level 0: searching-finding-trusting-acting-risking one's life? -- 4. Level 1: enhancing the provider- client relation through IT -- 5. Level 2: services without in-person contact between provider and client -- 6. Level 3: patient power on the web: the multifaceted role of personal health wisdom -- 7. Distinctive features of services conveyed through mobile apps -- Part II. Building Safety Nets Around the Active Client -- 8. Dimensions of patient risks and requirements for patient safety -- 9. Services for all stages of the metabolic syndrome and its consequences -- 10. Basic services reach out towards under-served populations -- 11. Smart homes: empowering the patient till the end -- 12. Partial solutions for patient safety -- Part III. Additional Methodology -- 13. Privacy and data protection: mission impossible? -- 14. The patient-centered electronic health record and patient portals -- 15. Scrutinized proof of effectiveness or cost effectiveness regarding patient reported outcomes -- 16. Economy 2: economic subsistence of services when research funding ends -- 17. Towards future consumer health informatics adapted health care legislation -- Trademarks -- Nomenclature -- General index -- Index of services.
- 2016 SpringerNilmini Wickramasinghe, Indrit Troshani, Joseph Tan, editors.Preface -- Foreword -- Section I: Defining the Discipline -- What Is Consumer Health Informatics -- The Landscape -- Section II: Technologies -- Remote Monitoring and Mobile Apps -- Social Media and Web 2.0 -- Personal Health Record -- Architecture and Infrastructure Requirements -- Section III: Design -- Designing for the Consumer -- Design Methods -- Section IV: Roles and Responsibilities -- Connecting with Medical Systems and Healthcare Providers -- Policy, Public Health, and Economics -- Quality Control, Security and Privacy -- Section V: On the Horizon: Perspectives on the Future -- The Future: Research Issues -- The Future: Policy and Funding -- The Future: Research Perspective, Grantor Perspective, Vendor Perspective -- Epilogue: Lessons, Take Aways and Recommendations -- Appendix: Case Vignettes.
- 2015 SpringerRichard Edlin, Christopher McCabe, Claire Hulme, Peter Hall, Judy Wright.
- 2012 ProQuest SafariEric Topol."Mobile technology has transformed our lives, and personal genomics is revolutionizing biology. But despite the availability of technologies that can provide wireless, personalized health care at lower cost, the medical community has resisted change. In The Creative Destruction of Medicine, Eric Topol--one of the nation's top physicians--calls for consumer activism to demand innovation and the democratization of medical care." -- [Publisher-provided data]
- 2012 Springeredited by Nilmini Wickramasinghe, Rajeev Bali, Reima Suomi, Stefan Kirn.Section I. Innovation and process considerations in the role of IS/IT in e-health. -- 1. Improving e-performance management in healthcare using intelligent IT solutions / Fatemeh Hoda Moghimi and Nilmini Wickramasinghe -- 2. An intelligence e-risk detection model to improve decision efficiency in the context of the orthopaedic operating room / Fatemeh Hoda Mogihim, Hossein Zadeh, and Nilmini Wickramasinghe -- 3. Healthcare information systems design : using a strategic improvisation model / Say Yen Teoh and Nilmini Wickramasinghe -- 4. Assimilation of healthcare information systems (HIS) : an analysis and critique / Hidayah Sulaiman and Nilmini Wichramasinghe -- 5. e-health in China : an evaluation / Yu Yun ... [et al.] -- 6. Improving the process of healthcare delivery in an outpatient environment : the case of a urology department / Chris Gonzalez and Nilmini Wickramasinghe -- 7. Adaptations for e-kiosk systems in Germany to develop barrier-free terminals for handicapped persons / Manuel Zwicker, Juergen Seitz, and Nilmini Wichramasinghe -- Section II. Design and organisation designing supportive and collaborative electronic health environments. -- 8. Collaborative approach for sustainable citizen-centered health care / Pirkko Nykänen and Antto Seppäla ̈-- 9. Strategies and solutions in e-health : a literature review / Marco De Marco, Francesca Ricciardi, and Jan vom Brocke -- 10. Online discussion forum as a means of peer support / R. Halonen -- 11. Designing persuasive health behavior change interventions / Tuomas Lehto -- 12. Accessiblility in the web for disabled people / Irene Krebs, Arnim Nethe, and Reetta Raitoharju -- Section III. The importance of people in e-health : lest we forget. -- 13. Knowledge management : often neglected but crucial to ehealth / Juerg P. Bleuer ... [et al.] -- 14. Patient Empowerment : a two way road / Lodewijk Bos -- 15. Citizen empowerment / Amir Hannan -- 16. E-health : focusing on people-centric dimensions / Rajeev K. Bali ... [et al.] -- 17. A model of estimating the direct benefits of implementing electronic data exchange of EMRs and state immunization information systems / Michael L. Popovich and Xiaohui Zhang -- Section IV. Innovation in e-health. -- 18. Business models for electronic healthcare services in Germany / S. Duennebeil, J. Leimeister, and H. Krcmar -- 19. Smart objects in healthcare : impact on clinical logistics / Martin Sedlmayr and Ulli Münch -- 20. Agency theory in e-healthcare and telemedicine : a literature study / Joerg Leukel ... [et al.] -- 21. Cost accounting and decision support for healthcare institutions / L. Waehlert, A. Wagner, and H. Czap -- 22. A comprehensive approach to the IT : clinial practice interface / David Zakim and Mark Dominik Alscher
- 2012Nicholas P. Tatonetti.Small molecule drugs continue to be an important part of medical therapy. However, their use is plagued by the onset of unexpected side effects, often seen only in late-stage clinical trials or after release to the market. As a result, there have been a number of high profile drug withdrawals because of side effects. More worrisome, however, are side effects that result from drug-drug interactions (DDIs). It is very difficult to empirically study DDIs before drugs enter the market because of the small samples of co-prescribed drugs in most late stage clinical drug (Phase III) studies. Some DDIs can be predicted based on knowledge of shared pathways of metabolism--such as when two drugs share a metabolizing enzyme and so the effective levels of one or both drugs are affected by saturation of the enzyme. But many DDIs are more idiosyncratic and difficult to predict. The most difficult cases are those in which two drugs produce a synergistic effect not seen with either drug alone. Thus, I created surveillance methods to detect unexpected DDIs, relying on clinical databases--both electronic medical records and spontaneous adverse event reporting systems. Understanding DDIs has an additional benefit for drug discovery. If two drugs have a synergistic effect, they may shed new light on the molecular mechanisms of their action or of the diseases they treat. If we use a model not of "one drug-one target" but of multiple interacting cellular pathways that respond to drugs ("the network is the target"), then we can leverage DDIs for the study of disease. However, to do this we need new ways to probe and understand these pathways, such as studying the unexpected synergies between drugs in observational reporting systems. Thus it would be extremely valuable to have computational methods that link adverse events to molecular events. The emergence of large databases linking drugs, diseases, drug effects, demographics and genes offers a new opportunity to create informatics methods for greater understanding small molecule effects at the clinical and biological level. I describe studies in which I have shown the great power of integrating these databases. In particular, I used the FDA Adverse Events Reporting System (FDA-AERS) to discover a signal for abnormal glucose in patients taking both paroxetine and pravastatin. Paroxetine is a selective serotonin reuptake inhibitor antidepressant. Pravastatin is an HMG CoA reductase inhibitor cholesterol-lowering drug. Neither is typically associated with hyperglycemia. Based on my analysis of the FDA-AERS, I examined patient electronic medical records in three separate hospitals (Stanford, Harvard, Vanderbilt), and demonstrated a striking increase in glucose levels on patients on both drugs, compared to their glucose levels on only one of the drugs. I also showed that mice on these two drugs have increased glucose. I am working with FDA to consider a potential update to the drug labels. Although this discovery illustrates the power of clinical data mining, the databases I used are filled with biases that make their use treacherous. I believe there are many similarly valuable discoveries to be made in these databases. However, only with careful attention to systematic biases can I ensure that the predictions I make are valid. In this thesis I describe methods to address the major informatics challenges to detecting and understanding the effects of taking multiple drugs at once. In particular, I have shown that I can (1) remove the bias introduced by unmeasured confounding variables, (2) improve the detection of drug interactions in cases of low or even non-reporting, (3) link drug effects to genes through chemical informatics methods, and (4) validate new drug effects using novel retrospective and prospective studies. The work forms an infrastructure that is useful to (1) pharmacogenomics scientists wishing to understand drug action at the molecular level, (2) pharmacologists wishing to better understand the effects of drugs singly and in combination, and (3) regulatory agencies wishing to understand the efficacy and safety of drugs and drug-interactions at a population level.
- 2011 ScienceDirectWitten, I. H.; Frank, Eibe; Hall, Mark A.Part I. Machine Learning Tools and Techniques: -- 1. What's it all about? -- 2. Input: concepts, instances, and attributes -- 3. Output: knowledge representation -- 4. Algorithms: the basic methods -- 5. Credibility: evaluating what's been learned -- Part II. Advanced Data Mining: -- 6. Implementations: real machine learning schemes -- 7. Data transformation -- 8. Ensemble learning -- 9. Moving on: applications and beyond -- Part III. The Weka Data Mining Workbench: -- 10. Introduction to Weka -- 11. The explorer -- 12. The knowledge flow interface -- 13. The experimenter -- 14 The command-line interface -- 15. Embedded machine learning -- 16. Writing new learning schemes -- 17. Tutorial exercises for the Weka explorer.
- 2012 Springer Protocolsedited by Hiroshi Mamitsuka, Charles DeLisi, Minoru Kanehisa.Dense module enumeration in biological networks / Koji Tsuda and Elisabeth Georgii -- Discovering interacting domains and motifs in protein-protein interactions / Willy Hugo, Wing-Kin Sung, and See-Kiong Ng -- Global alignment of protein-protein interaction networks / Misael Mongiovì and Roded Sharan -- Structure learning for Bayesian networks as models of biological networks / Antti Larjo, Ilya Shmulevich, and Harri Lähdesmäki -- Supervised inference of gene regulatory networks from positive and unlabeled examples / Fantine Mordelet and Jean-Philippe Vert -- Mining regulatory network connections by ranking transcription factor target genes using time series expression data / Antti Honkela, Magnus Rattray, and Neil D. Lawrence -- Identifying pathways of coordinated gene expression / Timothy Hancock, Ichigaku Takigawa, and Hiroshi Mamitsuka -- Mining frequent subtrees in glycan data using the rings glycan miner tool / Kiyoko Flora Aoki-Kinoshita -- Chemogenomic approaches to infer drug-target interaction networks / Yoshihiro Yamanishi -- Localization prediction and structure-based in silico analysis of bacterial proteins : with emphasis on outer membrane proteins / Kenichiro Imai, Sikander Hayat, Noriyuki Sakiyama, Naoya Fujita, Kentaro Tomii, Arne Elofsson, and Paul Horton -- Analysis strategy of protein-protein interaction networks / Zhenjun Hu -- Data mining in the MetaCyc family of pathway databases / Peter D. Karp, Suzanne Paley, and Tomer Altman -- Gene set/pathway enrichment analysis / Jui-Hung Hung -- Construction of functional linkage gene networks by data integration / Bolan Linghu, Eric A. Franzosa, and Yu Xia -- Genome-wide association studies / Tun-Hsiang Yang, Mark Kon, and Charles DeLisi -- Viral genome analysis and knowledge management / Carla Kuiken, Hyejin Yoon, Werner Abfalterer, Brian Gaschen, Chienchi Lo, and Bette Korber -- Molecular network analysis of diseases and drugs in KEGG / Minoru Kanehisa.
- 2015 Springer Protocolsedited by Carlos Fernández-Llatas, Juan Miguel García-Gómez.Actigraphy pattern analysis for outpatient monitoring / Elies Fuster-Garcia ... [et al.] -- Definition of loss functions for learning from imbalanced data to minimize evaluation metrics / Juan Miguel Garcia-Gómez and Salvador Tortajada -- Audit method suited for DSS in clinical environment / Javier Vicente -- Incremental logistic regression for customizing automatic diagnostic models / Salvador Tortajada, Montserrat Robles, and Juan Miguel Garcia-Gómez -- Using process mining for automatic support of clinical pathways design / Carlos Fernandez-Llatas ... [et al.] -- Analyzing complex patients' temporal histories : new frontiers in temporal data mining / Lucia Sacchi, Arianna Dagliati, and Riccardo Bellazzi -- Snow system : a decentralized medical data processing system / Johan Gustav Bellika, Torje Starbo Henriksen, and Kassaye Yitbarek Yigzaw -- Data mining for pulsing the emotion on the web / Jose Enrique Borras- Morell -- Introduction on health recommender systems / C. L. Sanchez-Bocanegra, F. Sanchez-Laguna, and J. L. Sevillano -- Cloud computing for context-aware enhanced m-health services / Carlos Fernandez-Llatas ... [et al.] -- Analysis of speech-based measures for detecting and monitoring alzheimer's disease / A. Khodabakhsh and C. Demiroglu -- Applying data mining for the analysis of breast cancer data / Der-Ming Liou and Wei-Pin Chang -- Mining data when technology is applied to support patients and professional on the control of chronic diseases : the experience of the METABO platform for diabetes management / Giuseppe Fico ... [et al.] -- Data analysis in cardiac arrhythmias / Miguel Rodrigo ... [et al.] -- Knowledge-based personal health system to empower outpatients of diabetes mellitus by means of P4 medicine / Adrián Bresó ... [et al.] -- Serious games for elderly continuous monitoring / Lenin-G. Lemus-Zúñiga ... [et al.].
- 2012Tiffany Jeahgin Chen.Although cancer types vary widely, the number of new cancer drugs each year is severely limited. Even for those cancer therapies which are currently in use, prognostic outcomes vary significantly across cancer types. Drug discovery relies primarily on our knowledge of direct drug targets, but not the systematic off-target effects that these therapies may have. As a result, our knowledge of these drugs is somewhat limited to general mechanistic classes. Within these classes it is hard to find potential patient differences without time-intensive studies and trials. While drug classification relies on our knowledge of direct targets, it does not typically consider how a number of global cellular processes are ultimately affected. Quantifying the mechanistic differences between drugs is a difficult process. Current standards to quantify individual drug efficacy are large-scale measurements are taken at a heterogeneous population level, ignoring the effects of drug action or mechanism in single cells or cell populations. Because our knowledge is limited in this way, we are often surprised to find that similarly classified cancer drugs can have disparate effects in patients. Single-cell technologies including flow cytometry allow us to uncover relationships between drugs through simultaneous measurement of cell signal, cell cycle and cell type for each cell. Recent technological advances in flow cytometry have facilitated new clinical tests to determine cancer subtypes. In addition, these methodological advances have created potential for providing novel insights into drug mechanism and patient response. In this dissertation, I describe a new framework for performing mechanistic profiling of cancer cells. There are two facets of this problem. The first is an understanding of cancer cell cycle. Prior to treating with a drug, it is important to form a general model of how a cancer cell replicates. In a screening methodology, however, this is a difficult problem. I address this problem by building an automated, de novo model of cell cycle. Second, I perform cancer therapeutic profiling by measuring DNA damage, apoptosis, cell cycle, and cell signaling markers across multiple cancer cell types. In this thesis, I combine both cell cycle and drug profiling methods into a new drug profiling framework that can be used to find existing and novel cell cycle and drug-based biology. The results of our current work have major implications for use in profiling aberrant cell types in primary cancer samples, as well as mechanistic drug screening.
- 2013 Springer Protocolsedited by Noam Shomron.Introduction to high-throughput sequencing experiments : design and bioinformatics analysis / Rachelly Normand and Itai Yanai -- Compressing resequencing data with GReEn / Armando J. Pinho, Diogo Pratas, and Sara P. Garcia -- On the accuracy of short read mapping / Peter Menzel ... [et al.] -- Statistical modeling of coverage in high-throughput data / David Golan and Saharon Rosset -- Assembly algorithms for deep sequencing data : basics and pitfalls / Nitzan Kol and Noam Shomron -- Short read mapping for exome sequencing / Xueya Zhou ... [et al.] -- Profiling short tandem repeats from short reads / Melissa Gymrek and Yaniv Erlich -- Exome sequencing analysis : a guide to disease variant detection / Ofer Isakov, Marie Perrone, and Noam Shomron -- Identifying RNA editing sites in miRNAs by deep sequencing / Shahar Alon and Eli Eisenberg -- Identifying differential alternative splicing events from RNA sequencing data using RNASeq-MATS / Juw Won Park ... [et al.] -- Optimizing detection of transcription factor-binding sites in ChIP-seq experiments / Aleksi Kallio and Laura L. Elo -- Statistical analysis of ChIP-seq data with MOSAiCS / Guannan Sun ... [et al.] -- Detection of reverse transcriptase termination sites using cDNA ligation and massive parallel sequencing / Lukasz J. Kielpinski ... [et al.].
- 2013 NAPCommittee on Improving the Quality of Cancer Care: Addressing the Challenges of an Aging Population, Board on Health Care Services ; Laura A. Levit, Erin P. Balogh, Sharyl J. Nass, and Patricia A. Ganz, editors, Institute of Medicine of the National Academies."In the United States, approximately 14 million people have had cancer and more than 1.6 million new cases are diagnosed each year. However, more than a decade after the Institute of Medicine (IOM) first studied the quality of cancer care, the barriers to achieving excellent care for all cancer patients remain daunting. Care often is not patient-centered, many patients do not receive palliative care to manage their symptoms and side effects from treatment, and decisions about care often are not based on the latest scientific evidence. The cost of cancer care also is rising faster than many sectors of medicine--having increased to 125 billion in 2010 from 72 billion in 2004--and is projected to reach 173 billion by 2020. Rising costs are making cancer care less affordable for patients and their families and are creating disparities in patients' access to high-quality cancer care. There also are growing shortages of health professionals skilled in providing cancer care, and the number of adults age 65 and older--the group most susceptible to cancer--is expected to double by 2030, contributing to a 45 percent increase in the number of people developing cancer. The current care delivery system is poorly prepared to address the care needs of this population, which are complex due to altered physiology, functional and cognitive impairment, multiple coexisting diseases, increased side effects from treatment, and greater need for social support. Delivering High-Quality Cancer Care: Charting a New Course for a System in Crisis presents a conceptual framework for improving the quality of cancer care. This study proposes improvements to six interconnected components of care: (1) engaged patients; (2) an adequately staffed, trained, and coordinated workforce; (3) evidence-based care; (4) learning health care information technology (IT); (5) translation of evidence into clinical practice, quality measurement and performance improvement; and (6) accessible and affordable care. This report recommends changes across the board in these areas to improve the quality of care. Delivering High-Quality Cancer Care: Charting a New Course for a System in Crisis provides information for cancer care teams, patients and their families, researchers, quality metrics developers, and payers, as well as HHS, other federal agencies, and industry to reevaluate their current roles and responsibilities in cancer care and work together to develop a higher quality care delivery system. By working toward this shared goal, the cancer care community can improve the quality of life and outcomes for people facing a cancer diagnosis."--Publisher's description.
- 2011 SpringerGondy Leroy ; Kathryn J. Hannah, Marion J. Ball (series editors).Part I Designing the User Study -- Overview -- Variables -- Design equation and statistics -- Between-subjects design -- Within-subject designs -- Advanced designs -- Part II Practical Tips -- Understanding main and interaction effects -- Conducting multiple comparisons -- Gold standard and user evaluations -- Recruiting and motivating study participants -- Institutional review board (IRB) approval -- Resources -- Part III Common Mistakes to Avoid -- Avoid bias -- Avoid missing the effect -- Avoid missing variables or conditions -- Other errors to avoid -- Appendix: cookbook for designing user studies in informatics.
- 2010Kaustubh Satyendra Supekar.Understanding human brain function is one of the most important endeavors in modern science. There is growing evidence that cognitive functions are executed by large-scale networks, comprising multiple interacting anatomically-connected brain areas. Although considerable progress has been made in understanding which specific brain areas are involved in particular cognitive functions, very little is known about the integrative functioning of large-scale brain networks. This is due in part to the lack of methods to pursue this line of research. This dissertation describes computational methods for detecting and characterizing large-scale human brain networks, combining data from task-free functional magnetic resonance imaging (fMRI) and structural diffusion tensor imaging (DTI), two complementary brain imaging modalities. Application of our methods to task-free fMRI and DTI data obtained from a wide range of subject populations provided new insights into how large-scale human brain networks develop, mature, and get disrupted in psychiatric and neurological disorders. More generally, this work demonstrates the power of our multimodal network-analytic approach to obtain a system-level understanding of brain function across the human lifespan.
- 2010Marina Sirota.Autoimmune diseases are painful and debilitating conditions which affect millions of people in the United States and all over the world. At present such conditions are often difficult to diagnose and many have no satisfactory treatment. Given the wealth and availability of genomic data such as genetic variation and gene expression, computational integrative methods provide a powerful opportunity to improve human health by refining the current knowledge about diagnostics, therapeutics and disease mechanism. For instance numerous genome-wide association studies (GWAS) performed across autoimmune diseases, provide a great opportunity to study disease relationships based on genetic variation. Comparing such profiles allows us to quantify allele-specific pair-wise relationships between these diseases to find two broad clusters of autoimmune disease. We furthermore find that certain polymorphisms, toggle SNPs, predispose individuals to one class of autoimmune disease but are protective against the other class. While studying allelic differences between diseases may point to key novel disease-specific genes and pathways, studying similarities across diseases might lead to discovery of common therapeutic options as well as common disease mechanisms. In particular we integrate genetic variation data across several studies to discover the role of a complement factor in Rheumatoid Arthritis and Multiple Sclerosis. Gene expression microarrays are also often used to study human diseases as well as the perturbation of biological systems by drug compounds providing an opportunity to discover novel relationships between diseases and drugs. We present a systematic computational method to predict novel therapeutic indications based on gene expression. We tested our top prediction for Crohn's disease (CD) using the rat model of inflammatory bowel disease (IBD), and successfully demonstrated the predicted efficacy of an anti-seizure drug in treating disease. In this work, we have showed that integrative computational tools can be used to improve diagnostics, learn more about disease mechanism and discover novel therapeutics for autoimmune disease.
- 2013Amit Kaushal.The ability to generate robust quantitative high-throughput protein abundance estimates directly from clinical samples would be useful for translational biomedical research. Knowing the protein content and abundance of a clinical sample would enable, for example, effective biomarker discovery, risk stratification of patient outcomes, and the ability to better understand disease mechanisms. Mass spectrometry has emerged as a powerful tool in the high-throughput measurement of proteins from human tissues and fluids. We are now beginning to have access to proteomics data of the coverage (hundreds to thousands of proteins), scale (tens to hundreds of samples), and throughput (a few days to weeks per experiment) to bring mass spectrometry proteomics to the study of clinical questions. In this work, we discuss methods for quantitation of peptide and protein abundance from mass spectrometry proteomics data. We apply our approaches to identify key proteins that are differentially expressed in the urine of kidney transplant patients with acute rejection. We also investigate the response of the human plasma proteome to severe burn injury. We characterize the protein composition of T-cells, monocytes, and neutrophils of trauma patients, healthy controls, and stimulated cells, and compare information content of proteomics data from these cell populations with gene expression data from similar samples. Finally, we discuss a novel metric for scoring normalization algorithms from mixture titration quality control experiments, and we apply this metric to proteomics and transcriptomics data. Through the methods for quantitation of peptides and proteins, application of proteomics to different clinical questions, and integration of proteomics with other high-throughput data, we demonstrate the utility of mass spectrometry based proteomics to the study of human biofluids in human disease research.
- 2009 SpringerNancy B. Finn, William F. Bria.
- 2015Robert Wachter.Status: Not Checked OutLane Catalog RecordFor the past few decades, technology has been touted as the cure for all of healthcare's ills, yet medicine stubbornly resisted computerization-- until now. Thanks largely to billions of dollars in federal incentives, healthcare has finally gone digital. Wachter examines healthcare at the dawn of its computer age, and shows how technology is changing care at the bedside. He questions whether government intervention has been useful or destructive-- and does so with clarity, insight, humor, and compassion.
- 2014 SpringerOleg S. Pianykh.Making a good diagnostic image is only the beginning; keeping it good and diagnostically sound is a much more difficult proposition, one that is often neglected or forgotten by clinical practitioners. With anything digital, the assumption of persistent original quality opens a Pandora's box of medical fiascos. Poorly selected image interpolation, thoughtlessly used compression, confused image enhancement options and the like can transform a good original into a useless clutter of pixels. This book is dedicated to learning better options.
- Digital imaging and communications in medicine (DICOM) : a practical introduction and survival guide. 2nd ed.2012 SpringerOleg S. Pianykh.Part I. Introduction to DICOM -- 1. What Is DICOM? -- 2. How does DICOM work? 3. Where do you get DICOM from? -- Part II. DICOM and clinical data -- 4. A brief history of DICOM -- 5. Parlez-vous DICOM? 6. Medical images in DICOM -- Part III. DICOM comunications -- 7. DICOM SOPs: Basic 8. DICOM SOPs: Beyond basic -- 9. DICOM associations -- Part IV: DICOM media and security -- 10. DICOM media: files, folders, and DICOMDIRs -- 11. DICOM security -- 12. Incompatibility of compatible -- Part V. Advanced topics -- 13. DICOM and teleradiology -- 14. Standards and system integration in digital medicine -- 15. Disaster PACS planning and management -- 16. DICOM applications: usual and not -- 17. DICOM software development -- 18. DICOM implementation plans -- 19. DICOM FAQs.
- 2011Suchi Saria.The current unprecedented rate of digitization of longitudinal health data --- continuous device monitoring data, laboratory measurements, medication orders, treatment reports, reports of physician assessments --- allows visibility into patient health at increasing levels of detail. A clearer lens into this data could help improve decision making both for individual physicians on the front lines of care, and for policy makers setting national direction. However, this type of data is high-dimensional (an infant with no prior clinical history can have more than 1000 different measurements in the ICU), highly unstructured (the measurements occur irregularly, and different numbers and types of measurements are taken for different patients) and heterogeneous (from ultrasound assessments to lab tests to continuous monitor data). Furthermore, the data is often sparse, systematically not present, and the underlying system is non-stationary. Extracting the full value of the existing data requires novel approaches. In this thesis, we develop novel methods to show how longitudinal health data contained in Electronic Health Records (EHRs) can be harnessed for making novel clinical discoveries. For this, one requires access to patient outcome data --- which patient has which complications. We present a method for automated extraction of patient outcomes from EHR data; our method shows how natural languages cues from the physicians notes can be combined with clinical events that occur during a patient's length of stay in the hospital to extract significantly higher quality annotations than previous state-of-the-art systems. We develop novel methods for exploratory analysis and structure discovery in bedside monitor data. This data forms the bulk of the data collected on any patient yet, it is not utilized in any substantive way post collection. We present methods to discover recurring shape and dynamic signatures in this data. While we primarily focus on clinical time series, our methods also generalize to other continuous-valued time series data. Our analysis of the bedside monitor data led us to a novel use of this data for risk prediction in infants. Using features automatically extracted from physiologic signals collected in the first 3 hours of life, we develop Physiscore, a tool that predicts infants at risk for major complications downstream. Physiscore is both fully automated and significantly more accurate than the current standard of care. It can be used for resource optimization within a NICU, managing infant transport to a higher level of care and parental counseling. Overall, this thesis illustrates how the use of machine learning for analyzing these large scale digital patient data repositories can yield new clinical discoveries and potentially useful tools for improving patient care.
- 2012Erik Corona.In the last 100,000 years, humans have been subjected to multiple different evolutionary pressures. Migration events, changing food sources, climate change, and technological advances are some of the ways environmental changes have applied pressure on human populations to undergo change. Recent advances in methods to measure differences in DNA sequences have led to new powerful techniques to measure the effect of evolution on different human populations. Also due to the availability of recent explosion of genomic data, our understanding of genetic basis of human disease has grown significantly. However, our knowledge regarding the effect that recent evolution has had on the genetic susceptibility to disease has grown to a much lesser extent. There is a lack of studies attempting to place the genetic basis of disease in the context of recent evolutionary changes. I describe multiple ways in which recent evolutionary pressures on the human genome can lead to insights to understanding how evolution has impacted complex disease. I show that GWAS (Genome-Wide Association Studies) are particularly well suited to measure the effect of recent evolution in complex disease. I provide methodology to detect positive selection in human disease and are able to ascertain whether recent evolution has disproportionately increased or decreased the risk of inherited disease. In addition, I introduce a method to approximate when and where genetic risk differentiation for specific disease has occurred, starting when humans began migration out of Africa. Environmental changes in the last 10,000 years known to have created novel, diverse, and pervasive pathogens. I provide methodology to find positive selection in communicable disease. I identify populations that have most likely been severely impacted by specific pathogens in recent human history. I develop and apply methods to identify specific genetic variants important to both communicable and inherited disease that have been affected by evolutionary pressures. I find that type 1 diabetes has recently undergone strong positive selection towards increasing genetic risk in European derived populations. In addition type 2 diabetes and pancreatic cancer is associated with migration trajectories and I find genetic risk differentiation exceeding what is expected by genetic drift in a total of 11 complex diseases. Finally, I find evidence of positive selection in many distinct populations within proteins interacting bacillus anthracis and yersinia pestis, which cause anthrax and the bubonic plague, respectively. I have shown how recent evolution can lead to an increased understanding of both inherited and infectious disease.
- 2014 SpringerAntonio Gaddi, Fabio Capello, Marco Manca, editors ; forewords by Sergio Bertolucci and Gianfranco Gensini.The debate over eHealth is alive as never before. Supporters suggest that it will result in dramatic innovations in healthcare, including a giant leap towards patient-centered care, new opportunities to improve effectiveness, and enhanced wellness and quality of life. In addition, the growing market value of investments in health IT suggests that eHealth can offer at least a partial cure for the current economic stagnation. Detractors counter these arguments by claiming that eHealth has already failed: the UK Department of Health has shut down the NHS National Program for IT, Google has discontinued its Health flagship, and doubts have arisen over privacy safeguards for both patients and medical professionals. This book briefly explains why caregivers, professionals, technicians, patients, politicians, and others should all consider themselves stakeholders in eHealth. It offers myth-busting responses to some ill-considered arguments from both sides of the trench, in the process allowing a fresh look at eHealth. In addition, it describes how the technical failures of previous eHealth systems can be avoided, examines the legal basis of eHealth, and discusses associated ethical issues.
- 2008 Springeredited by Michael Christopher Gibbons.An overview of healthcare disparities -- Provider factors in healthcare disparities -- Patient factors in healthcare disparities -- Healthcare system factors in healthcare disparities -- The social "nonmedical" determinants of health -- The role of the Internet in American life -- The iHealth revolution -- Digital disparities -- The role of eHealth in patient engagement and quality improvement -- Medical informatics -- Public health informatics -- Beyond traditional paradigms in disparities research -- Health information technology policy perspectives and healthcare disparities -- Disparities and eHealth: achieving the promise and the potential.
- 2013 WileyPradeep Sinha, Gaur Sunder, Prashant Bendale, Manisha Mantri, Atreya Dande."Discover How Electronic Health Records Are Built to Drive the Next Generation of Healthcare Delivery. The increased role of IT in the healthcare sector has led to the coining of a new phrase 'health informatics, ' which deals with the use of IT for better healthcare services. Health informatics applications often involve maintaining the health records of individuals, in digital form, which is referred to as an Electronic Health Record (EHR). Building and implementing an EHR infrastructure requires an understanding of healthcare standards, coding systems, and frameworks. This book provides an overview of different health informatics resources and artifacts that underlie the design and development of interoperable healthcare systems and applications. Electronic Health Record: Standards, Coding Systems, Frameworks, and Infrastructures compiles, for the first time, study and analysis results that EHR professionals previously had to gather from multiple sources. It benefits readers by giving them an understanding of what roles a particular healthcare standard, code, or framework plays in EHR design and overall IT-enabled healthcare services along with the issues involved. This book on Electronic Health Record: Offers the most comprehensive coverage of available EHR Standards including ISO, European Union Standards, and national initiatives by Sweden, the Netherlands, Canada, Australia, and many others; Provides assessment of existing standards; Includes a glossary of frequently used terms in the area of EHR; Contains numerous diagrams and illustrations to facilitate comprehension; Discusses security and reliability of data."--Publisher's description.
- 2014 CRCnetBASEedited by Dean F. Sittig, PhD.Part 1. Introduction -- part 2. Identifying and preventing EHR safety concerns -- part 3. EHR users and usability -- part 4. Clinical decision support -- part 5. Referrals -- part 6. Laboratory test result management -- part 7. Bar coded medication administration -- part 8. Computer-based provider order entry.
- 2010 SpringerCharles A. Shoniregun, Kudakwashe Dube, Fredrick Mtenzi.Introduction to e-Healthcare Information Security / Charles A. Shoniregun, Kudakwashe Dube and Fredrick Mtenzi -- Securing e-Healthcare Information / Charles A. Shoniregun, Kudakwashe Dube and Fredrick Mtenzi -- Laws and Standards for Secure e-Healthcare Information / Charles A. Shoniregun, Kudakwashe Dube and Fredrick Mtenzi -- Secure e-Healthcare Information Systems / Charles A. Shoniregun, Kudakwashe Dube and Fredrick Mtenzi -- Towards a Comprehensive Framework for Secure e-Healthcare Information / Charles A. Shoniregun, Kudakwashe Dube and Fredrick Mtenzi -- Towards a Unified Security Evaluation Framework for e-Healthcare Information Systems / Charles A. Shoniregun, Kudakwashe Dube and Fredrick Mtenzi -- Discussions / Charles A. Shoniregun, Kudakwashe Dube and Fredrick Mtenzi.
- 2008 SpringerGeorge P. Rédei.v. 1. A-L -- v. 2. M-Z.
- 2003 ScienceDirecteditor-in-chief, Hossein Bidgoli.
- 2011Chirag Jagdish Patel.Common diseases arise out of combination of both genetic and environmental influences. Advances in genomic technology have enabled investigators to create hypotheses regarding the contribution of genetic factors at a breathtaking pace. However, the assessment of multiple and specific environmental factors--and their interactions with the genome-- has not. We lack high-throughput analytic methodologies to comprehensively and systematically associate multiple physical and specific environmental factors, or the "envirome", to disease and human health. We claim that the creation of hypotheses regarding the environmental contribution to disease is practicable through high-throughput analytic methods that have been well established in genomics. In the following dissertation, we develop and apply methods to systematically and comprehensively associate specific factors of the envirome with disease states, prioritizing factors for in-depth future study. The current disciplines of studying the environmental determinants of health include toxicology and epidemiology, which operate on molecular and population scales, respectively. This dissertation proposes approaches in both of these disciplines. For example, we have developed a framework to conduct the first "Environment-wide Association Study" (EWAS), systematically associating environmental factors to disease on a population scale. We have applied this framework to investigate type 2 diabetes and heart disease on cohorts that are representative United States population, finding novel and robust associations in diverse and independent cohorts. Given the lack of explained risk resulting from current day genome-wide studies, the time is ripe to usher in a more comprehensive study of the environment, or "enviromics", toward better understanding of multifactorial diseases and their prevention.
- Ethics, medicine, and information technology : intelligent machines and the transformation of health care2015 CambridgeKenneth W. Goodman.Information technologies and 21st-century clinical practice : ethics and the electronic health record -- Ancient professions and intelligent machines : the ethical challenge of computational decision support -- Health privacy, data protection, and trust -- Professionalism, programming, and pedagogy -- Safety, standards, and interoperability -- The e-health industry : markets, vendors, and regulators -- Digital health : ubiquitous, virtual, remote, robotic -- Biomedical research from genomes to populations : big data and the growth of knowledge.
- Evaluating clinical practice variation using a knowledge-based temporal sequence alignment framework2012Wei-Nchih Lee.Entrusted with providing high quality and cost-effective care across the continuum of primary care to quaternary care medicine, health care institutions are turning to electronic medical records to keep pace with the information demands of medicine. The new patient care data collected within electronic medical records provides the computational foundation to build the rapid learning health care system, in which the delivery of health care within an entire institution improves dynamically by transforming the data into knowledge about which clinical practices are most effective. A crucial component to the rapid learning health care system is an understanding of clinical practice variations in medicine. Individual variations in care reflect decision choices of the treating clinician(s). Taken across an entire population, practice variations offer valuable insight on the behaviors and beliefs of an institution. Devising strategies and policies to improve the quality and efficiency of health care would not be possible without the knowledge that studying practice variations provide. Yet, existing methods for measuring clinical practice variations are not designed to handle temporal complexity. They focus on a small set of practices, of limited duration, and with limited scope. With the data that electronic medical records can provide, we have an opportunity to evaluate temporal complexity in medicine by studying patterns of care and entire treatment histories for a population of patients. In this thesis, I present a method, the T3S, for measuring the temporal sequence similarity between two patterns of care. The T3S advances research in temporal data mining by providing methodology that allows for the measurement of complex temporal features in clinical care. Specifically, the T3S measures the similarity of patterns in terms of the temporal ordering, duration, and overlap of its constituent treatments. I implement the T3S in three novel tools that allow population-level clinical practice variations to be studied from electronic medical records. To begin with, I use the T3S with expert derived domain knowledge to match medication treatment data from the medical record to chemotherapy plans so that patterns of care can be abstracted from granular medical data. This automated method for medical record abstraction of treatment information is a crucial first step before clinical data can be analyzed. Next, I use the T3S to find similar patterns of care from an electronic medical record to recommendations from a clinical practice guideline. The evaluation of individual patterns of care against evidence-based guidelines is an important task of health services related outcomes research. Finally, I incorporate the T3S into a new method for discovering patterns of care from a population of treatment histories. I show how this method can be used to summarize the clinical practice patterns within a population cohort and even discover anomalous practice patterns that may be of interest to clinicians and health services researchers. I evaluate each of these methods for its ability to provide clinically meaningful results from the available treatment data. Taken together, the T3S and the methods in which it is implemented offer a novel framework from which temporal complexities in the practice of medicine can be meaningfully explored. Finding and discovering similar patterns of care offers substantial potential in quality of care, outcomes, and comparative effectiveness research. As medicine marches to the digital age of data, measuring temporal similarity will assume a critical role in the development of new informatics methods to address the challenges of population science.
- 2006 SpringerCharles P. Friedman, Jeremy C. Wyatt ; foreword by Edward H. Shortliffe ; with contributions by Joan S. Ash, Allen C. Smith III, P. Zoë Stavri, and Mark S. Roberts.Challenges of Evaluation in Biomedical Informatics, p. 1-20 -- Evaluation as a Field, p. 21-47 -- Determining What to Study, p. 48-84 -- The Structure of Objectivist Studies, p. 85-112 -- Measurement Fundamentals, p. 113-144 -- Developing and Improving Measurement Methods, p. 145-187 -- The Design of Demonstration Studies, p. 188-223 -- Analyzing the Results of Demonstration Studies, p. 224-247 -- Subjectivist Approaches to Evaluation, p. 248-266 -- Performing Subjectivist Studies in the Qualitative Traditions Responsive to Users / Joan Ash, Allen Smith and P. Starvi, p. 267-300 -- Economic Aspects of Evaluation / Mark Roberts, p. 301-337 -- Proposing and Communicating the Results of Evaluation Studies: Ethical, Legal, and Regulatory Issues, p. 338-361.
- Factors affecting physician professional satisfaction and their implications for patient care, health systems, and health policy2013 RAND Healththe RAND Corporation: Mark William Friedberg, Peggy G. Chen, Kristin R. Van Busum, Frances Aunon, Chau Pham, John Caloyeras, Soeren Mattke, Emma Pitchforth, Denise D. Quigley, Robert H. Brook ; American Medical Association: F. Jay Crosson, Michael Tutty.One of the American Medical Association's core strategic objectives is to advance health care delivery and payment models that enable high-quality, affordable care and restore and preserve physician satisfaction. Such changes could yield a more sustainable and effective health care system with highly motivated physicians. To that end, the AMA asked RAND Health to characterize the factors that lead to physician satisfaction. RAND sought to identify high-priority determinants of professional satisfaction that can be targeted within a variety of practice types, especially as smaller and independent practices are purchased by or become affiliated with hospitals and larger delivery systems. Researchers gathered data from 30 physician practices in six states, using a combination of surveys and semistructured interviews. This report presents the results of the subsequent analysis, addressing such areas as physicians' perceptions of the quality of care, use of electronic health records, autonomy, practice leadership, and work quantity and pace. Among other things, the researchers found that physicians who perceived themselves or their practices as providing high-quality care reported better professional satisfaction. Physicians, especially those in primary care, were frustrated when demands for greater quantity of care limited the time they could spend with each patient, detracting from the quality of care in some cases. Electronic health records were a source of both promise and frustration, with major concerns about interoperability between systems and with the amount of physician time involved in data entry.
- 2016 SpringerWinnok H. De Vos, Sebastian Munck, Jean-Pierre Timmermans [editors].
- 2008 CRCnetBASEedited by Sergey Ilyin.Intelligent automation / James M. Dixon -- Neurally inspired algorithms as computational tools / Mark Flynn and Garrett T. Kenyon -- Using pharmacodynamic biomarkers to accelerate early clinical drug development / Ole Vesterqvist -- Opportunities in CNS drug discovery and development / Albert Pinhasov ... [et al.] -- Clinical success of antibody therapeutics in oncology / Bernard J. Scallon ... [et al.] -- Relating target sequence to biological function / Greg M. Arndt -- Use of protein microarrays for molecular network analysis and signal-pathway profiling / Katherine R. Calvo, Lance A. Liotta, and Emanuel F. Petricoin -- Laser-microdissection-based transcriptomics using microarrays / Fredrik Kamme ... [et al.].
- 2007 SpringerElisabeth Rakus-Andersson.
- 2008 ProQuest Ebook Centraledited by Tony Solomonides [and others].Advancing virtual communities -- A Healthcare-driven framework for facilitation the secure sharing of data across organizational boundaries -- A Data model for integrating heterogeneous medical data in the Health-e-Child Project -- Gridifying phlogeny and medical applications on the volunteer computing platform -- HOPE, an open platform for medical data management on the grid -- NeuroLOG: a community-driven middleware design -- -- Public health informatics -- How grids are perceived in healthcare and the public service sectior -- From "low hanging" to "user ready": initial steps into a HealthGrid. -- Virtual objects in large scale health information systems -- Toward a virtual anonymisation grid for unified access to remote clinical data -- -- Translational bioinformatics -- A Highly optimized grid deployment: the metagenomic analysis example -- A Grid-based protein complex predictor -- Virtual high throughput screening (vHTS) on an optical high speed testbed -- A Protein structure prediction service in the ProGenGrid system -- BioNessie -- a grid enabled biochemical networks simulation environment -- -- Knowledge management and decision support -- The @neurIST Project -- @neuLink: a service-oriented application for biomedical knowledge discovery -- @neurIST -- chronic disease management through integration of heterogeneous data and computer-interpretable guideline services -- Data privacy considerations in intensive care grids -- Multi-science decision support of HIV drug resistance treatment -- -- Three 'Road maps' -- -- Integrated research team final report HealthGrid: grid technologies for Biomedicine(1-2 March 2006) -- A Roadmap for caGrid, an enterprise grid architecture for biomedical research -- The SHARE road map: healthgrids for biomedical research and healthcare.
- 2006 ProQuest Ebook CentralBrian R. Hunt, Ronald L. Lipsman, Jonathan M. Rosenberg, with Kevin R. Coombes, John E. Osborn, and Garrett J. Stuck.
- 2013 CRCnetBASEauthor, Khaled El Emam."Foreword Personal health information comprises the most sensitive and intimate details of one's life, such as those relating to one's physical or mental health, and the health history of one's family. Intuitively, we understand the importance of protecting health information in order to ensure the confidentiality of such personal data and the privacy of the individual to whom it relates. Personal health information must also be accurate, complete, and accessible to health care practitioners in order to provide individuals with necessary health care. At a broader level, for secondary uses that go beyond the treatment of the individual, health-related data are needed for the benefit of society as a whole. These vitally important secondary uses include activities to improve the quality of care, health research, and the management of publicly funded health care systems. As the information and privacy commissioner of Ontario, Canada, my role includes the oversight of health privacy legislation governing the collection, use, and disclosure of personal health information by organizations and individuals involved in the delivery of health care services. Ontario's Personal Health Information Protection Act (PHIPA) aims to respect an individual's right to privacy in relationship to his or her own personal health information while accommodating the legitimate need to access health information for well-defined purposes. PHIPA does this in part by establishing clear rules for the use and disclosure of personal health information for secondary purposes. The object of these rules is to maximize the benefits of both respecting personal privacy and making health information accessible for purposes that serve society as a whole"--Provided by publisher.
- 2015 CambridgeJyotsna Pundir, Sub-Speciality Fellow in Reproductive Medicine and Surgery, St Bartholomew's Hospital, London, UK, Arri Coomarasamy, Professor of Gynaecology, School of Clinical and Experimental Medicine, College of Medicial and Dental Sciences, University of Birmingham, and Birmingham Women's Hospital Foundation Trust, Birmingham, UK.
- 2006 CRCnetBASEedited by Stephan Olariu, Albert Y. Zomaya.
- 2010 CRCnetBASEedited by Jean-Loup Faulon, Andreas Bender.Chapter 1. Representing Two-Dimensional (2D) Chemical Structures with Molecular Graphs / Ovidiu Ivanciuc -- Chapter 2. Algorithms to Store and Retrieve Two-Dimensional (2D) Chemical Structures / Milind Misra, Jean-Loup Faulon -- Chapter 3. Three-Dimensional (3D) Molecular Representations / Egon L. Willighagen -- Chapter 4. Molecular Descriptors / Nikolas Fechner, Georg Hinselmann, Jor̈g Kurt Wegner -- Chapter 5. Ligand- and Structure-Based Virtual Screening / Robert D. Clark, Diana C. Roe -- Chapter 6. Predictive Quantitative Structure-Activity Relationships Modeling: Data Preparation and the General Modeling Workflow / Alexander Tropsha, Alexander Golbraikh -- Chapter 7. Predictive Quantitative Structure-Activity Relationships Modeling: Development and Validation of QSAR Models / Alexander Tropsha, Alexander Golbraikh -- Chapter 8. Structure Enumeration and Sampling / Markus Meringer -- Chapter 9. Computer-Aided Molecular Design / Donald P. "Visco, Jr." -- Chapter 10. Computer-Aided Molecular Design / Diana C. Roe -- Chapter 11. Reaction Network Generation / Jean-Loup Faulon, Pablo Carbonell -- Chapter 12. Open Source Chemoinformatics Software and Database Technologies / Rajarshi Guha -- Chapter 13. Sequence Alignment Algorithms / Tatsuya Akutsu -- Chapter 14. Machine Learning-Based Bioinformatics Algorithms / Shawn Martin -- Chapter 15. Using Systems Biology Techniques to Determine Metabolic Fluxes and Metabolite Pool Sizes / Fangping Mu, Amy L. Bauer, James R. Faeder, William S. Hlavacek.
- Advance in structural bioinformatics — Handbook of chemoinformatics algorithms (100)
- Handbook of computational molecular biology — Primer on clinical experience in medicine : reasoning, decision making, and communication in health sciences (100)
- Principles of biomedical informatics. Second edition. [2nd ed.] — Your passport to a career in bioinformatics (43)
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Continuously expanding, all databases in the repository contain the latest editions of selected medical titles.MicroMedex: Premier pharmaceutical information source containing multiple databases and drug reference tools. Of particular value is DRUGDEX Evaluations, one of the most comprehensive drug sources available.DynaMed Plus is a clinical information resource used to answer questions quickly at the point-of-care. Easy-to-interpret Levels of Evidence help clinicians rapidly determine the quality of the available evidence. Scopus is the largest abstract and citation database of peer-reviewed literature: scientific journals, books and conference proceedings.A drug information resource containing: American Hospital Formulary System (AHFS), drug formulary for Lucile Packard Children's Hospital (LPCH) and Stanford Hospital & Clinics (SHC), Lexi-Drugs (adverse reactions, dosage and administration, mechanism of action, storage, use, and administration information), Lexi-Calc, Lexi-ID, Lexi-I.V. Compatibility (King Guide), Lexi-Interact, and Lexi-PALS.Cumulative Index to Nursing and Allied Health Literature (CINAHL) contains coverage of nursing and allied health literature.A knowledge database that provides access to topic reviews based on over 6000 clinically relevant articles. The evidence-based content, updated regularly, provides the latest practice guidelines in 59 medical specialties.Provides critical assessments of systematic reviews compiled from a variety of medical journals.Selects from the biomedical literature original studies and systematic reviews that are immediately clinically relevant and then summarizes these articles in an enhanced abstract with expert commentary.
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