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Data Mining in Biomedicine
. Ed(S): Pardalos, Panos M.; Boginski, Vladimir L.; Vazacopoulos, Alkis
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Description for Data Mining in Biomedicine
hardcover. Data Mining in Biomedicine Editor(s): Pardalos, Panos M.; Boginski, Vladimir L.; Vazacopoulos, Alkis. Series: Springer Optimization and its Applications. Num Pages: 598 pages, biography. BIC Classification: MQW; UNC. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 33. Weight in Grams: 1012.
This volume presents an extensive collection of contributions covering aspects of the exciting and important research field of data mining techniques in biomedicine. Coverage includes 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 incorporation of data mining in fundamental areas of biomedical research: genomics, proteomics, protein characterization, and neuroscience.
This volume presents an extensive collection of contributions covering aspects of the exciting and important research field of data mining techniques in biomedicine. Coverage includes 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 incorporation of data mining in fundamental areas of biomedical research: genomics, proteomics, protein characterization, and neuroscience.
Product Details
Format
Hardback
Publication date
2007
Publisher
Springer-Verlag New York Inc. United States
Number of pages
598
Condition
New
Series
Springer Optimization and its Applications
Number of Pages
582
Place of Publication
New York, NY, United States
ISBN
9780387693187
SKU
V9780387693187
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Data Mining in Biomedicine
From the reviews: "This book is an in-depth look at ‘the development of appropriate methods for extracting useful information’ from data in biomedicine. … is aimed at scientists and practitioners in the fields of biomedicine, engineering, mathematics, and computer science as well as graduate students and is appropriate for a variety of readers. … A ... Read more