Medical Informatics (inbunden)
Format
Inbunden (Hardback)
Språk
Engelska
Antal sidor
648
Utgivningsdatum
2005-06-01
Upplaga
2005 ed.
Förlag
Springer-Verlag New York Inc.
Medarbetare
Chen, Hsinchun (ed.), Fuller, Sherrilynne S. (ed.), Friedman, Carol (ed.), Hersh, William (ed.)
Illustratör/Fotograf
49 schwarz-weiße Zeichnungen 104 schwarz-weiße Abbildungen, 55 schwarz-weiße Fotos 44 schwarz-weiß
Illustrationer
104 Illustrations, black and white; XLIV, 648 p. 104 illus.
Dimensioner
243 x 162 x 37 mm
Vikt
1090 g
Antal komponenter
1
Komponenter
1 Hardback
ISBN
9780387243818

Medical Informatics

Knowledge Management and Data Mining in Biomedicine

Inbunden,  Engelska, 2005-06-01
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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.
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Innehållsförteckning

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.