Summary and Info
Medical Informatics and biomedical computing have grown in quantum measure over the past decade. An abundance of advances have come to the foreground in this field with the vast amounts of biomedical and genomic data, the Internet, and the wide application of computer use in all aspects of medical, biological, and health care research and practice. MEDICAL INFORMATICS: Knowledge Management and Data Mining in Biomedicine covers the basic foundations of the area while extending the foundational material to include the recent leading-edge research in the field. The newer concepts, techniques, and practices of biomedical knowledge management and data mining are introduced and examined in detail. It is the research and applications in these areas that are raising the technical horizons and expanding the utility of informatics to an increasing number of biomedical professionals and researchers.The book is divided into three major topical sections.Section I presents the foundational information and knowledge management material and includes topics such as: bioinformatics challenges and standards, security and privacy, ethical and social issues, and biomedical knowledge mapping.Section II discusses the topics which are relevant to knowledge representations & access and includes topics such as: representations of medical concepts and relationships, genomic information retrieval, 3D medical informatics, public access to anatomic images, and creating and maintaining biomedical ontologies.Section III examines the emerging application research in data mining, biomedical textual mining, and knowledge discovery research and includes topics such as: semantic parsing and analysis for patient records, biological relationships, gene pathways, and metabolic networks, exploratory genomic data analysis, joint learning using data and text mining, and disease informatics and outbreak detection.The book is a comprehensive presentation of the foundations and leading application research in medical informatics/biomedicine. These concepts and techniques are illustrated with detailed case studies.The authors are widely recognized professors and researchers in Schools of Medicine and Information Systems from the University of Arizona, University of Washington, Columbia University, and Oregon Health & Science University. In addition, individual expert contributing authors have been commissioned to write chapters for the book on their respective topical expertise.
More About the Author
Hsinchun Chen is the Regents' Professor and Thomas R. Brown Chair of Management and Technology at the University of Arizona and the Director and founder of the Artificial Intelligence Lab (AI Lab).
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