Kohonen self organizing maps and expert system for blood classification

Information gathering in medicine generally follows a set of sequence: an interview with the patient, an examination, and one or more laboratory tests to support the working diagnosis. Building a knowledge base from observing a medical examination, however, is risky. Medical decision-making relies o...

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Bibliographic Details
Published inProceedings of IEEE Region 10 International Conference on Electrical and Electronic Technology. TENCON 2001 (Cat. No.01CH37239) Vol. 1; pp. 174 - 180 vol.1
Main Authors Elfadil, N., Hani, M.K., Nor, S.M., Hussein, S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2001
Subjects
Blood
Decision making
Diagnostic expert systems
Expert systems
Laboratories
Medical diagnostic imaging
Medical expert systems
Medical tests
Neural networks
Self organizing feature maps
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Summary:Information gathering in medicine generally follows a set of sequence: an interview with the patient, an examination, and one or more laboratory tests to support the working diagnosis. Building a knowledge base from observing a medical examination, however, is risky. Medical decision-making relies on imprecise information gathered in a variety of ways and interpreted in a largely intuitive fashion. This paper proposes a novel method that integrates neural network and expert system paradigms to produce an automated knowledge acquisition system. This system will produce symbolic knowledge from medical data automatically.
ISBN:0780371011
9780780371019
DOI:10.1109/TENCON.2001.949575