Data Mining and Medical Knowledge Management: Cases and Applications

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.

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