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Use of neural network techniques in a medical expert system
Author(s) -
Hudson D. L.,
Cohen M. E.,
Anderson M. F.
Publication year - 1991
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.4550060208
Subject(s) - expert system , computer science , artificial intelligence , artificial neural network , legal expert system , disadvantage , conjunction (astronomy) , process (computing) , machine learning , model based reasoning , knowledge representation and reasoning , physics , astronomy , operating system
Expert systems in medicine have relied heavily upon knowledge‐based techniques, in which decision making rules or strategies are derived through consultation with experts. These techniques, coupled with methods of approximate reasoning, have produced systems which model the human decision making process. This approach has the disadvantage of requiring extensive interviewing of experts for each new application. It is desirable to be able to supplement this information by extracting information directly from data bases, without expert intervention. In this article, a neural network model is used to extract this information, and then use it in conjunction with rule‐based knowledge, incorporating techniques of approximate reasoning.