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Data Mining and Medical Knowledge Management: Cases and Applications

Petr Berka (University of Economics, Prague, Czech Republic), Jan Rauch (University of Economics, Prague, Czech Republic), and Djamel Abdelkader Zighed (University of Lumiere Lyon 2, France)
Indexed In: SCOPUS View 2 More Indices
Release Date: February, 2009 | Copyright: © 2009 | Pages: 464

Publication Status: E-Book and Print Version Available for Purchase
ISBN13: 9781605662183
EISBN13: 9781605662190
DOI: 10.4018/978-1-60566-218-3

Description:

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.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Classification and prediction with neural networks
  • Clinical prediction rules
  • Cost-sensitive learning in medicine
  • ECG processing
  • EEG data mining using PCA
  • Gene expression mining
  • Human embryo selection
  • Image registration for biomedical information integration
  • Medical knowledge management
  • Medical Web site management
  • Mining tuberculosis data
  • Ontologies in the health field
  • Preprocessing perceptrons and multivariate decision limits
  • Risk prediction models using data mining

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Reviews

This publication is a collection of case studies in which advanced DM and KM solutions are applied to concrete cases in biomedical research. The reader will find all the peculiarities of the medical field, which require specific solutions to complex problems.

– Riccardo Bellazzi, Università di Pavia, Italy

The book will be of interest to researchers and students in computer science and medicine, and to physicians and managers in the healthcare industry.

– Book News Inc. (June 2009)

Petr Berka is a full professor at the Department of Information and Knowledge Engineering, University of Economics and also works in the Centre of Biomedical Informatics, Institute of Computer Science, Academy of Sciences of the Czech Republic. His main research interests are machine learning, data mining and knowledge-based systems.
Jan Rauch is an associate professor at the Deptartment of Information and Knowledge Engineering, University of Economics and also works in the Centre of Biomedical Informatics, Institute of Computer Science, Academy of Sciences of the Czech Republic. His main research interest is data mining.
Djamel Abdelkader Zighed received his Master in Computer and Automatic Science in 1982 and his PhD in computer science in 1985 – both from University Lyon 1. He was as assistant professor at University Lyon 1 in 1984-1987. In 1987, he joined the University Lyon 2 where he worked as lecturer (1987-1991), professor (1991-2000) and 1st class professor (2000 - present). He is interested in data mining (including mining complex data), machine learning and knowledge engineering. He is the founder and was director (1995-2002) of the ERIC laboratory (laboratory for development of methods and software for knowledge engineering, and more specifically automatic Knowledge Discovery in Databases).

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Editorial Advisory Board
  • Riccardo Bellazzi, University of Pavia, Italy
  • Radim Jiroušek, Institute of Information Theory and Automation, Czech Republic
  • Katharina Morik, University of Dortmund, Germany
  • Ján Paralic, Technical University Košice, Slovak Republic
  • Luis Torgo, University of Porto, Portugal
  • Blaž Župan, University of Ljubljana, Slovenia