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Intelligent Data Analysis in Medicine and Pharmacology (Hardcover, 1997 ed.)
Loot Price: R5,620
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Intelligent Data Analysis in Medicine and Pharmacology (Hardcover, 1997 ed.)
Series: The Springer International Series in Engineering and Computer Science, 414
Expected to ship within 10 - 15 working days
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Intelligent data analysis, data mining and knowledge discovery in
databases have recently gained the attention of a large number of
researchers and practitioners. This is witnessed by the rapidly
increasing number of submissions and participants at related
conferences and workshops, by the emergence of new journals in this
area (e.g., Data Mining and Knowledge Discovery, Intelligent Data
Analysis, etc.), and by the increasing number of new applications
in this field. In our view, the awareness of these challenging
research fields and emerging technologies has been much larger in
industry than in medicine and pharmacology. The main purpose of
this book is to present the various techniques and methods that are
available for intelligent data analysis in medicine and
pharmacology, and to present case studies of their application.
Intelligent Data Analysis in Medicine and Pharmacology consists of
selected (and thoroughly revised) papers presented at the First
International Workshop on Intelligent Data Analysis in Medicine and
Pharmacology (IDAMAP-96) held in Budapest in August 1996 as part of
the 12th European Conference on Artificial Intelligence (ECAI-96),
IDAMAP-96 was organized with the motivation to gather scientists
and practitioners interested in computational data analysis methods
applied to medicine and pharmacology, aimed at narrowing the
increasing gap between excessive amounts of data stored in medical
and pharmacological databases on the one hand, and the
interpretation, understanding and effective use of stored data on
the other hand. Besides the revised Workshop papers, the book
contains a selection of contributions by invited authors. The
expected readership of the book is researchers and practitioners
interested in intelligent data analysis, data mining, and knowledge
discovery in databases, particularly those who are interested in
using these technologies in medicine and pharmacology. Researchers
and students in artificial intelligence and statistics should find
this book of interest as well. Finally, much of the presented
material will be interesting to physicians and pharmacologists
challenged by new computational technologies, or simply in need of
effectively utilizing the overwhelming volumes of data collected as
a result of improved computer support in their daily professional
practice.
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