Medical data mining and knowledge discovery
著者
書誌事項
Medical data mining and knowledge discovery
(Studies in fuzziness and soft computing, v. 60)
Physica-Verlag, c2001
- : hbk
大学図書館所蔵 全10件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
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注記
Includes bibliographical references
内容説明・目次
内容説明
Modern medicine generates, almost daily, huge amounts of heterogeneous data. For example, medical data may contain SPECT images, signals like 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 and data comprehension. Computerized techniques are needed to help humans address this problem. This volume is devoted to the relatively young and growing field of medical data mining and knowledge discovery. As more and more medical procedures employ imaging as a preferred diagnostic tool, there is a need to develop methods for efficient mining in databases of images. Other significant features are security and confidentiality concerns. Moreover, the physician's interpretation of images, signals, or other technical data, is written in unstructured English which is very difficult to mine. This book addresses all these specific features.
目次
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. Lopez-Chavarrias, C. Montes: Knowledge Discovery in Time Series Using Expert Knowledge.
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