Medical Informatics: Knowledge Management and Data Mining in Biomedicine

by Hsinchun Chen (Editor), Sherrilynne S. Fuller (Editor), Carol Friedman (Editor), William Hersh (Editor)

Overview

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. These concepts and techniques are illustrated with detailed case studies.

Product Details

ISBN-13:	9781441937353
Publisher:	Springer US
Publication date:	12/08/2010
Series:	Integrated Series in Information Systems , #8
Edition description:	Softcover reprint of hardcover 1st ed. 2005
Pages:	648
Product dimensions:	6.10(w) x 9.20(h) x 1.50(d)

Table of Contents

Foundational Topics in Medical Informatics.- Knowledge Management, Data Mining, and Text Mining in Medical Informatics.- Mapping Medical Informatics Research.- Bioinformatics Challenges and Opportunities.- Managing Information Security and Privacy in Healthcare Data Mining.- Ethical and Social Challenges of Electronic Health Information.- Information and Knowledge Management.- Medical Concept Representation.- Characterizing Biomedical Concept Relationships.- Biomedical Ontologies.- Information Retrieval and Digital Libraries.- Modeling Text Retrieval in Biomedicine.- Public Access to Anatomic Images.- 3D Medical Informatics.- Infectious Diseaxe Informatics and Outbreak detection.- Text Mining and Data Mining.- Semantic Interpretation for the Biomedical Research Literature.- Semantic Text Parsing for Patient Records.- Identification of Biological Relationships from Text Documents.- Creating, Modeling, and Visualizing Metabolic Networks.- Gene Pathway Text Mining and Visualization.- The Genomic Data Mine.- Exploratory Genomic Data Analysis.- Joint Learning Using Multiple Types of Data and Knowledge.