Data mining in biomedicine.

*(English)*Zbl 1130.92034
Springer Optimization and Its Applications 7. New York, NY: Springer (ISBN 978-0-387-69318-7/hbk). xvii, 579 p. (2007).

Publisher’s description: This volume presents an extensive collection of chapters covering various aspects of the exciting and important research area of data mining techniques in biomedicine. The topics include: new approaches for the analysis of biomedical data; applications of data mining techniques to real-life problems in medical practice; comprehensive reviews of recent trends in the field.

The book addresses the problems arising in fundamental areas of biomedical research, such as genomics, proteomics, protein characterization, and neuroscience. It would be of interest to scientists and practitioners working in the field of biomedicine, as well as related areas of engineering, mathematics, and computer science. It can also be helpful to graduate students and young researchers looking for new exciting directions in their work. Since each chapter can be read independently, readers interested in specific problems and applications may find the material of certain chapters useful.

The volume is organized in five parts. Part I: Recent methodlogical developments for data mining problems in biomedicine. Part II: Data mining techniques in diease diagnosis. Part III: Data mining studies in genomics and proteomics. Part IV: Characterization and prediction of protein structure. Part V: Applications of data mining techniques to brain dynamics studies.

The book addresses the problems arising in fundamental areas of biomedical research, such as genomics, proteomics, protein characterization, and neuroscience. It would be of interest to scientists and practitioners working in the field of biomedicine, as well as related areas of engineering, mathematics, and computer science. It can also be helpful to graduate students and young researchers looking for new exciting directions in their work. Since each chapter can be read independently, readers interested in specific problems and applications may find the material of certain chapters useful.

The volume is organized in five parts. Part I: Recent methodlogical developments for data mining problems in biomedicine. Part II: Data mining techniques in diease diagnosis. Part III: Data mining studies in genomics and proteomics. Part IV: Characterization and prediction of protein structure. Part V: Applications of data mining techniques to brain dynamics studies.