Medical Informatics: Knowledge Management and Data Mining in Biomedicine / Edition 1

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

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.

Editorial Reviews

4 Stars! from Doody

Reviewer: David M. Liebovitz, MD (University of Chicago Medicine)
Description: This book provides informatics students with a foundation in the primary concepts used in knowledge management. Use of these concepts is then illustrated through case examples.
Purpose: The purpose is to complement introductory medical informatics textbooks and focus on biomedical knowledge management for professionals and researchers. This book is needed clarify the concepts and practices used behind the scenes to bring useful knowledge to researchers and caregivers. This book met the authors' objectives.
Audience: According to the authors, this book is directed to a large potential audience. It could serve as a graduate level textbook in informatics; health computing courses in medical, nursing and pharmacy schools would benefit; library science departments would find the book useful for courses; and it would likely provide reference value for researchers and biomedical professionals. These groups truly represent the likely users. The authors are credible authorities.
Features: The book includes foundation material in knowledge management and data mining. Subjects such as ontologies, vocabularies, and biomedical knowledge mapping are included with examples. Various techniques in data mining are explored. Examples from clinical medicine and literature searching to biomedical research are included. Web sites for additional material integrated into chapters are useful. An index of all web sites referenced in the book would have been helpful. Some of the reported work is supported by grants and references are included. The chapters adhere to a consistent organizational framework that includes an overview and questions for discussion. Several figures use black text on a gray background, making it difficult to read.
Assessment: The book is useful beyond the level of an introductory informatics text. Importantly, definitions of key bioinformatics concepts with detailed examples will be useful to readers from diverse backgrounds.

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