Data Mining And Medical Knowledge Management

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More About This Textbook

Overview

The healthcare industry produces a constant flow of data, creating a need for deep analysis of databases through data mining tools and techniques resulting in expanded medical research, diagnosis, and treatment.

Data Mining and Medical Knowledge Management: Cases and Applications presents case studies on applications of various modern data mining methods in several important areas of medicine, covering classical data mining methods, elaborated approaches related to mining in electroencephalogram and electrocardiogram data, and methods related to mining in genetic data. A premier resource for those involved in data mining and medical knowledge management, this book tackles ethical issues related to cost-sensitive learning in medicine and produces theoretical contributions concerning general problems of data, information, knowledge, and ontologies.

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Product Details

  • ISBN-13: 9781605662183
  • Publisher: IGI Global
  • Publication date: 3/10/2011
  • Pages: 466
  • Product dimensions: 8.70 (w) x 11.20 (h) x 1.30 (d)

Table of Contents

Sect. I Theoretical Aspects

Ch. I Data, Information and Knowledge 1

Ch. II Ontologies in the Health Field 37

Ch. III Cost-Sensitive Learning in Medicine 57

Ch. IV Classification and Prediction with Neural Networks 76

Ch. V Preprocessing Perceptrons and Multivariate Decision Limits 108

Sect. II General Applications

Ch. VI Image Registration for Biomedical Information Integration 122

Ch. VII ECG Processing 137

Ch. VIII EEG Data Mining Using PCA 161

Ch. IX Generating and Verifying Risk Prediction Models Using Data Mining 181

Ch. X Management of Medical Website Quality Labels via Web Mining 206

Ch. XI Two Case-Based Systems for Explaining Exceptions in Medicine 227

Sect. III Specific Cases

Ch. XII Discovering Knowledge from Local Patterns in SAGE Data 251

Ch. XIII Gene Expression Mining Guided by Background Knowledge 268

Ch. XIV Mining Tinnitus Database for Knowledge 293

Ch. XV Gaussian-Stacking Multiclassifiers for Human Embryo Selection 307

Ch. XVI Mining Tuberculosis Data 332

Ch. XVII Knowledge-Based Induction of Clinical Prediction Rules 350

Ch. XVIII Data Mining in Atherosclerosis Risk Factor Data 376

Compilation of References 398

Index 437

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