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  • Book
    Jessica D. Tenenbaum, Piper A. Ranallo, editors.
    Summary: This textbook provides a detailed resource introducing the subdiscipline of mental health informatics. It systematically reviews the methods, paradigms, tools and knowledge base in both clinical and bioinformatics. Key foundational technologies, such as terminologies, ontologies and data exchange standards are all covered. The learning health system model is utilized to emphasize the bi-directional nature of the translational science associated with mental health processes. Descriptions of the data, technologies, paradigms and products that are generated by and used in each process and their limitations are discussed. Mental Health Informatics: Enabling a Learning Mental Healthcare System is a comprehensive introductory resource for students, educators and researchers in mental health informatics and related behavioral sciences. It is an ideal resource for use in a survey course for both pre- and post-doctoral training programs, as well as for healthcare administrators, funding entities, vendors and product developers working to make mental healthcare more evidence-based.

    Contents:
    Precision Medicine and the Learning Health System
    What is Informatics?
    What is Mental Health?
    Epistemological Differences between the Behavioral and Biological Sciences
    What is Mental Health Informatics?
    Big Picture: Process View of Mental Health Care Delivery
    Introduction to Technologies for Data Acquisition in Mental Health
    Informatics Technologies for the Acquisition of Biological Data
    Informatics Technologies for the Acquisition of Psychological and Behavioral Data
    Informatics Technologies for the Acquisition of Interpersonal, Social and Environmental Data: The Exosome
    Informatics Technologies for the Acquisition of Population Level Data
    Introduction to Methods for Extracting Meaningful Information from Data in Mental Health
    Concept and Knowledge Representation to Transform Data into Information in Mental Health
    Bioinformatics Methods in Mental Health Research and Practice
    Psychometric Methods
    Computational Models and Analytic Methods
    Natural Language Processing in Mental Health Research and Practice
    Introduction to Paradigms for Knowledge Discovery in Mental Health
    Paradigms for Knowledge Discovery in Clinical and Research Data Repositories
    Biomarker Discovery
    Data Visualization
    Inferential Analysis and Predictive Modeling
    The Role of Biological Information in Mental Health Research and Practice
    Electronic Health Record (EHR) Systems in Mental Health
    Computerized Clinical Decision Support in Mental Health
    Informatics Technologies in Detection and Diagnosis of Mental Health Conditions
    Informatics Technologies in Prevention and Treatment of Mental Health Conditions
    Informatics Technologies for Care Coordination and Continuity of Care
    Informatics Technologies to Improve Patient Safety in Mental Health
    Registries
    Disseminating Newly Acquired Knowledge
    Ethical Legal and Social Issues (ELSI)
    The Future of Mental Health Informatics.
    Digital Access Springer 2021