Medical Data Mining and Knowledge Discovery

ISBN-13: 9783790813401 / Angielski / Twarda / 2000 / 498 str.

Krzysztof J. Cios

Opis

Modern medicine generates, almost daily, huge amounts of heterogeneous data. For example, medical data may contain SPECT images, signals lik e ECG, clinical information like temperature, cholesterol levels, etc., as well as the physician's interpretation. Those who deal with such data understand that there is a widening gap between data collection a nd data comprehension. Computerized techniques are needed to help huma ns address this problem. This volume is devoted to the relatively youn g and growing field of medical data mining and knowledge discovery. As more and more medical procedures employ imaging as a preferred diagno stic tool, there is a need to develop methods for efficient mining in databases of images. Other significant features are security and confi dentiality concerns. Moreover, the physician's interpretation of image s, signals, or other technical data, is written in unstructured Englis h which is very difficult to mine. This book addresses all these speci fic features.

Spis treści

K.J. Cios, G.W. Moore: Medical Data Mining and Knowledge Discovery: Overview of Key Issues.- J.M. Saul: Legal Policy and Security Issues in the Handling of Medical Data.- W. Ceusters: Medical Natural Language Understanding as a Supporting Technology for Data Mining in Healthcare.- G.W. Moore, J.J. Berman: Anatomic Pathology Data Mining.- D. Shalvi, N. DeClaris: A Data Clustering and Visualization Methodology for Epidemiological Pathology Discoveries.- V. Megalooikonomou, E.H. Herskovits: Mining Structure-Function Associations in a Brain Image Database.- K.G. Goh, W. Hsu, M.L. Lee, H. Wang: ADRIS: An Automatic Diabetic Retinal Image Screening System.- M. Last, O. Maimon, A. Kandel: Knowledge Discovery in Mortality Records: An Info-Fuzzy Approach.- B. Kovalerchuk, E. Vityaev, J.F. Ruiz: Consistent and Complete Data and "Expert" Mining in Medicine.- M.L. Wong, W. Lam, K.S. Leung: A Medical Data Mining Application Based on Evolutionary Computation.- S. Miksch, A. Seyfang, W. Horn, C. Popow, F. Paky: Methods of Temporal Data Validation and Abstraction in High-Frequency Domains.- G.B. Singh, S. Krawetz: Data Mining the Matrix Associated Regions (MARs) for Gene Therapy.- J.C.G. Ramirez, L.L. Peterson, D.J. Cook, D.M. Peterson: Discovery of Temporal Patterns in Sparse Course-of-Disease Data.- L.A. Consularo, R. de Alencar Lotufo, L. da Fontoura Costa: Data Mining-Based Modeling of Human Visual Perception.- S. Tsumoto: Discovery of Clinical Knowledge in Databases Extracted from Hospital Information Systems.- F. Alonso, J.P. Caraca-Valente, I. López-Chavarrías, C. Montes: Knowledge Discovery in Time Series Using Expert Knowledge.