Books by Subject
Information and Library Science
- 2001 CRCnetBASEStahl, Dean; De Sola, Ralph; Kerchelich, Karen.
- Dictionary of acronyms, abbreviations, and initialisms.
- 2010 SpringerArabnia, Hamid R.Bioinformatics databases, data mining, and pattern discovery -- Microarray, gene expression analysis, and gene regulatory networks -- Protein classification & structure prediction, and computational structural biology -- Comparative sequence, genome analysis, genome assembly, and genome scale computational methods -- Drug design, drug screening, and related topics -- Computational methods and diagnostic tools in biomedical -- General topics in bioinformatics.Also available: Print – 2010
- 2007Iverson, Cheryl.PrintStatus: Not Checked OutLane Catalog RecordTypes of articles -- Manuscript preparation -- References -- Visual presentation of data -- Ethical and legal considerations -- Editorial assessment and processing -- Grammar -- Punctuation -- Plurals -- Capitalization -- Correct and preferred usage -- Non-English words, phrases, and accent marks -- Medical indexes -- Abbreviations -- Nomenclature -- Eponyms -- Greek letters -- Units of measure -- Numbers and percentages -- Study design and statistics -- Mathematical composition -- Typography -- Manuscript editing and proofreading -- Glossary of publishing terms -- Resources.Also available: Print – 2007
- 2007 SpringerBaldock, Richard; Burger, Albert G.; Davidson, Duncan.Existing anatomy ontologies for human, model organisms and plants -- Anatomical ontologies for model organisms : the fungi and animals / Jonathan Bard -- Plant structure ontology (PSO) : a morphological and anatomical ontology of flowering plants / Katica Ilic, ... [et al.] -- Anatomy for clinical terminology / Alan L. Rector -- The foundational model of anatomy ontology / Cornelius Rosse and José L. V. Mejino, Jr. -- Towards a disease ontology / Paul N. Schofield, Björn Rozell, Georgios V. Gkoutos -- Engineering and linking of anatomy ontologies -- Ontology alignment and merging / Patrick Lambrix, He Tan -- COBrA and COBrA-CT : ontology engineering tools / Stuart Aitken, Yin Chen -- XSPAN : a cross-species anatomy network / Albert Burger, Jonathan Bard -- Searching biomedical literature with anatomy ontologies / Thomas Wächter, ... [et al.] -- Anatomy ontologies and spatio-temporal atlases -- Anatomical ontologies : linking names to places in biology / Richard A. Baldock, Albert Burger -- Time in anatomy / Duncan Davidson -- The Edinburgh mouse atlas / Richard Baldock, Duncan Davidson -- The smart atlas : spatial and semantic strategies for multiscale integration of brain data / Maryann E. Martone, ... [et al.] -- Anatomy ontologies : modelling principles -- Modelling principles and methodologies : relations in anatomical ontologies / Fabian Neuhaus, Barry Smith -- Modeling principles and methodologies : spatial representation and reasoning / Thomas Bittner, ... [et al.] -- CARO : the common anatomy reference ontology / Melissa A. Haendel, ... [et al.]
- 2009 ebraryGacek, Adam.The main sequence is comprised of approximately 200 entries dealing with almost all aspects of Arabic manuscript studies (codicology and paleography); includes appendices covering abbreviations, letterforms, såurah-headings, major reference works, and a guide to the description of manuscripts, as well as charts of major historical periods and dynasties.
- 2010Xu, Rong; Altman, Russ B.; Das, Amar K.; Garber, Alan M.; Manning, Christopher D.Advances in medical research, pharmaceuticals, treatment options, and biotechnology are occurring at an explosive rate. As of 2009, there are 19 million of biomedical research abstracts available on MEDLINE and 1.3 billion searches of MEDLINE are done in 2009. Most of the popular search engines, from Google to PubMed, use keyword-based information retrieval methods, often overloading users with irrelevant information. At the same time, keyword-based search engines cannot answer simple biomedical questions, such as "what are the breast cancer treatment drugs" or "what are the breast cancer associated genes". Answering such questions requires machine understandable knowledge to be extracted from free text. My thesis represents an automated system to extract machine understandable biomedical information from MEDLINE abstracts using machine learning and natural language processing ( NLP ) techniques. The system is different from current biomedical information extraction systems in the following: 1. the system is semi-supervised where the only human supervision is a single pattern for each information type; 2. it can be used to extract broad types of information, including named entities and relationships among entities.
- 2006 NLM
- 2007 SpringerBajorath, Jürgen; Bunin, Barry A.; Morales, Guillermo A.; Siesel, B.
- Also available: Print – 2003-
- 2005 books24x7, SUNet ID login required.Maimon, Oded Z.; Rokach, Lior.
- 2008 CRCnetBASEKlimberg, Ronald K.; Kudyba, Stephan; Lawrence, Kenneth D.An approach to analyzing and modeling systems for real-time decisions / John C. Brocklebank ... [et al.] -- Ensemble strategies for neural network classifiers / Paul Mangiameli and David West -- Neural network classification with uneven misclassification costs and imbalanced group sizes / Jyhshyan Lan ... [et al.] -- Data cleansing with independent component analysis / Guangyin Zeng and Mark J. Embrechts -- A multiple criteria approach to creating good teams over time / Ronald K. Klimberg, Kevin J. Boyle, and Ira Yermish -- Data mining applications in higher education / Cali M. Davis ... [et al.] -- Data mining for market segmentation with market share data : a case study approach / Illya Mowerman and Scott J. Lloyd -- An enhancement of the pocket algorithm with ratchet for use in data mining applications / Louis W. Glorfeld and Doug White -- Identification and prediction of chronic conditions for health plan members using data mining techniques / Theodore L. Perry, Stephan Kudyba, and Kenneth D. Lawrence -- Monitoring and managing data and process quality using data mining : business process management for the purchasing and accounts payable processes / Daniel E. O'Leary -- Data mining for individual consumer models and personalized retail promotions / Rayid Ghani ... [et al.] -- Data mining : common definitions, applications, and misunderstandings / Richard D. Pollack -- Fuzzy sets in data mining and ordinal classification / David L. Olson, Helen Moshkovich, and Alexander Mechitov -- Developing an associative keyword space of the data mining literature through latent semantic analysis / Adrian Gardiner -- A classification model for a two-class (new product purchase) discrimination process using multiple-criteria linear programming / Kenneth D. Lawrence ... [et al.].
- 2006 WileyCover, Thomas M.; Thomas, Joy A.ch. 1. Introduction and preview -- ch. 2. Entropy, relative entropy, and mutual information -- ch. 3. Asymptotic equipartition property -- ch. 4. Entropy rates of a stochastic process -- ch. 5. Data compression -- ch. 6. Gambling and data compression -- ch. 7. Channel capacity -- ch. 8. Differential entropy -- ch. 9. Gaussian channel -- ch. 10. Rate distortion theory -- ch. 11. Information theory and statistics -- ch. 12. Maximum entropy -- ch. 13. Universal source coding -- ch. 14. Kolmogorov complexity -- ch. 15. Network information theory -- ch. 16. Information theory and portfolio theory -- ch. 17. Inequalities in information theory.
- 2006 books24x7, SUNet ID login required.v. 2 books24x7Wang, John."The Encyclopedia of Data Warehousing and Mining provides a comprehensive, critical and descriptive examination of concepts, issues, trends, and challenges in this rapidly expanding field of data warehousing and mining (DWM). This encyclopedia consists of more than 350 contributors from 32 countries"--Provided by the publisher.
- 2003 ScienceDirectBidgoli, Hossein.
- Global information warfare : how businesses, governments, and others achieve objectives and attain competitive advantages2002 CRCnetBASEJones, Andy; Kovacich, Gerald L.; Luzwick, Perry G.
- 2005 CRCnetBASEMehta, Dinesh P.; Sahni, Sartaj.
- 2010 CRCnetBASEAndreadis, Joanne D.; Liebowitz, Jay; Schieber, Richard A.The quick basics of knowledge management / Jay Liebowitz -- Knowledge management and public health : a winning combination / Jay Liebowitz, Richard A. Schieber, and Joanne D. Andreadis -- Extending cross-generational knowledge flow research in edge organizations / Jay Liebowitz and Emil Ivanov -- Knowledge retention trends and strategies for knowledge workers and organizations / Masud Cader and Jay Liebowitz -- Examples of knowledge management in public health / Angela M. Fix, Sterling Elliott, and Irene Stephens -- Building knowledge management in an international health NGO / Richard Iams and Patricia Ringers -- Trying to revive an anemic system : a case study from USAID's Nutrition Division / Laura Birx -- Formulating KM strategies at the local level : a new approach to knowledge sharing in large public health organizations / Richard Van West-Charles and Arthur J. Murray -- Knowledge management : a mechanism for promoting evidence-informed public health decision making / Maureen Dobbins ... [et al.] -- myPublicHealth : utilizing knowledge management to improve public health practice and decision making / Debra Revere ... [et al.] -- Connections : sharing experience to advance public health practice / Ellen Wild and Debra Bara -- The association of public health laboratories : from surveys toward knowledge management, a voyage to Cythera / Robert Rej and Neha Desai.
- 2001 CRCnetBASELiebowitz, Jay.
- 2014 CRCnetBASEGaber, Mohamed Medhat; Sakr, Sherif."This book provides a central source of reference on the various data management techniques of large scale data processing and its technology application. This book presents chapters written by leading researchers, academics, and practitioners in the field, all of which have been reviewed by independent reviewers. The book covers the latest research discoveries and applications. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques"-- Provided by publisher.
- 2013 ebraryJanes, Joseph.Thinking about the future of libraries, librarianship and the work librarians do is as old as libraries themselves. (No doubt seminars were organized by the Alexandria Librarians Association on the future of the scroll and what to do about the rising barbarian tide.) At no time in our memory, though, have these discussions and conversations been so profound and critical. Here one of today's leading thinkers and speakers about the future of libraries brings together 30 leaders from all types of libraries and from outside librarianship to describe their vision of what the library will be in 2020. Contributors and Library Journal's The Annoyed Librarian were asked to describe the "library of 2020, "in whatever terms they wanted, either a specific library or situation or libraries in general. They were told: "be bold, be inspirational, be hopeful, be true, be provocative, be realistic, be depressing, be light-hearted, be thoughtful, be fun, be yourself, and for heaven's sake, don't be boring." Not that they could be. Broadly representative of important perspectives and aspects within the profession as well as featuring important voices beyond the professional realm, Library 2020 presents thought-provoking and illuminating visions from many points of view. It is both required reading for library leaders and trustees as well as an ideal supplemental text for LIS classes looking at the future of the profession.
- 2007 books24x7, SUNet ID login required.Myatt, Glenn J.Also available: Print – 2007
- Metadata-driven software systems in biomedicine : designing systems that can adapt to changing knowledge2011 SpringerNadkarni, Prakash M.What Is Metadata? -- Data Types in the Medical Record -- Metadata and the Use of XML -- Representing Structured Clinical Data -- Building the User Interface for Structured Clinical Data Capture -- Medical Decision Support Systems: General Considerations -- Challenges in Electronic Decision Support Implementation -- Infrastructure for Complex Clinical Decision Support: Rule Engines -- Decision Support Infrastructure: Workflows and Service-Oriented Architectures -- Complex Decision Support in Practice -- Extending the Entity-Attribute-Value Model -- Descriptive Metadata: An Introduction to Terminologies -- Descriptive Metadata: Implementing Large-Scale Biomedical Ontologies -- Clinical Study Data Management Systems -- Data Retrieval for Heterogeneous Data Models -- Metadata for Data Warehousing -- Biomedical Metadata Standards.
- 2006 MyiLibraryKishore, Rajiv; Ramesh, Ram; Sharman, Raj.
- 2005 Assoc Res LibrBailey, Charles W.
- Harrison, Brian Howard; Matthew, H. C. G.
- Includes all of words, phrases, and translations, in French, German, Spanish and Italian from the print dictionaries. Users can search the full A-Z from both sides of the dictionary in Oxford's unabridged bilingual dictionaries: French, German, Spanish, and Italian.
- 2012 CambridgeStiles, Anne."In the 1860s and 1870s, leading neurologists used animal experimentation to establish that discrete sections of the brain regulate specific mental and physical functions. These discoveries had immediate medical benefits: David Ferrier's detailed cortical maps, for example, saved lives by helping surgeons locate brain tumors and haemorrhages without first opening up the skull. These experiments both incited controversy and stimulated creative thought, because they challenged the possibility of an extra-corporeal soul. This book examines the cultural impact of neurological experiments on late Victorian Gothic romances by Robert Louis Stevenson, Bram Stoker, H. G. Wells and others. Novels like Dracula and Jekyll and Hyde expressed the deep-seated fears and visionary possibilities suggested by cerebral localization research and offered a corrective to the linearity and objectivity of late Victorian neurology"--Provided by publisher.
- 2002 NAP
- 2014 ebraryRay, Joyce M.It has become increasingly accepted that important digital data must be retained and shared in order to preserve and promote knowledge, advance research in and across all disciplines of scholarly endeavor, and maximize the return on investment of public funds. To meet this challenge, colleges and universities are adding data services to existing infrastructures by drawing on the expertise of information professionals who are already involved in the acquisition, management and preservation of data in their daily jobs. Data services include planning and implementing good data management practices, thereby increasing researchers' ability to compete for grant funding and ensuring that data collections with continuing value are preserved for reuse. This volume provides a framework to guide information professionals in academic libraries, presses, and data centers through the process of managing research data from the planning stages through the life of a grant project and beyond. It illustrates principles of good practice with use-case examples and illuminates promising data service models through case studies of innovative, successful projects and collaborations.
- Statistical and machine-learning data mining : techniques for better predictive modeling and analysis of big data. 2nd ed.2012 CRCnetBASERatner, Bruce.Introduction -- Two basic data mining methods for variable assessment -- CHAID-based data mining for paired-variable assessment -- The importance of straight data : simplicity and desirability for good model-building practice -- Symmetrizing ranked data : a statistical data mining method for improving the predictive power of data -- Principal component analysis : a statistical data mining method for many-variable assessment -- The correlation coefficient : its values range between plus/minus 1, or do they? -- Logistic regression : the workhorse of response modeling -- Ordinary regression : the workhorse of profit modeling -- Variable selection methods in regression : ignorable problem, notable solution -- CHAID for interpreting a logistic regression model -- The importance of the regression coefficient -- The average correlation : a statistical data mining measure for assessment of competing predictive models and the importance of the predictor variables -- CHAID for specifying a model with interaction variables -- Market segmentation classification modeling with logistic regression -- CHAID as a method for filling in missing values -- Identifying your best customers : descriptive, predictive, and look-alike profiling -- Assessment of marketing models -- Bootstrapping in marketing : a new approach for validating models -- Validating the logistic regression model : try bootstrapping -- Visualization of marketing modelsdata mining to uncover innards of a model -- The predictive contribution coefficient : a measure of predictive importance -- Regression modeling involves art, science, and poetry, too -- Genetic and statistic regression models : a comparison
- 2012 CRCnetBASESumma, Mireille Gettler."Data analysis is changing fast. Driven by a vast range of application domains and affordable tools, machine learning has become mainstream. Unsupervised data analysis, including cluster analysis, factor analysis, and low dimensionality mapping methods continually being updated, have reached new heights of achievement in the incredibly rich data world that we inhabit.Statistical Learning and Data Science is a work of reference in the rapidly evolving context of converging methodologies. It gathers contributions from some of the foundational thinkers in the different fields of data analysis to the major theoretical results in the domain. On the methodological front, the volume includes conformal prediction and frameworks for assessing confidence in outputs, together with attendant risk. It illustrates a wide range of applications, including semantics, credit risk, energy production, genomics, and ecology. The book also addresses issues of origin and evolutions in the unsupervised data analysis arena, and presents some approaches for time series, symbolic data, and functional data. Over the history of multidimensional data analysis, more and more complex data have become available for processing. Supervised machine learning, semi-supervised analysis approaches, and unsupervised data analysis, provide great capability for addressing the digital data deluge. Exploring the foundations and recent breakthroughs in the field, Statistical Learning and Data Science demonstrates how data analysis can improve personal and collective health and the well-being of our social, business, and physical environments. "-- Provided by publisher.
- An online library of Thieme books. Includes Thieme eRadiology and RadCases content made available through the Medlantis database.
- 2006 CRCnetBASESrodin, Sharon.
- 2012 CRCnetBASEOsterhage, Wolfgang.1. Introduction -- 2. WLAN -- 3. PDAs -- 4. Mobile phones -- 5. Bluetooth -- 6. Infrared -- 7. Security policy.
- 2009 SpringerBudgell, Brian Stephen.This book is organized as a practical guide to writing a biomedical research article. Hence, as you will see from the table of contents, chapters are arranged according to the sequence of tasks that we normally encounter in our writing. The book deals only with writing and submission of manuscripts; there are no directions concerning, for example, the preparation of figures or audiovisual presentations. Furthermore, every chapter is concise; we do not beat topics to death. Exemplars of highly prevalent expressions are given throughout, however the number of examples in the book is not excessive.
- Harrison's Principles of Internal Medicine
- AAP Red Book Online
- Robbins & Cotran Pathologic Basis of Disease
- Sabiston Textbook of Surgery
- Nelson's Textbook of Pediatrics
- Surgical Exposures in Orthopaedics
- Mandell, Douglas, & Bennett's Principles & Practice of Infectious Diseases
- Red Book Online
- ICU Book
- Primary Care Medicine
- Campbell-Walsh Urology
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