NDLI: Performance of a fuzzy set theoretic model for medical diagnosis

Content Provider	IEEE Xplore Digital Library
Author	Esogbue, A.O.
Copyright Year	1983
Description	Author affiliation: Georgia Institute of Technology Atlanta (Esogbue, A.O.)
Abstract	Classical mathematical models for medical diagnosis which have been computerized are known to perform very poorly when compared to diagnoses made by the physician. Factors which contribute to their poor performance relate to the omission by these models of important information on the patient such as symptoms of past undiagnosed diseases which can only be vaguely recalled by the patient. Other deficiencies include failure to model the stage of development of the disease and certain intrinsically fuzzy aspects of the pertinent information nets that are needed to develop a medical hypothesis. Models which attempted to remedy these shortcomings were developed and presented by the authors elsewhere. In this effort, we describe a study in which our fuzzy diagnosis models were computerized, validated and compared with a mock physician hypothesis as well as existing mathematical models. The example Involved a medical hypothsis concerning a medical condition of valvular heart disease. The results show that while there were discrepancies between the fuzzy model's and the physician's hypotheses, the model's performance was vastly superior to that of existing mathematical models.
Starting Page	856
Ending Page	858
File Size	294786
Page Count	3
File Format	PDF
ISBN	0818605030
DOI	10.1109/SCAMC.1983.764789
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1983-10-23
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy sets Medical diagnosis Mathematical model Diseases History Medical diagnostic imaging Physics computing Fuzzy set theory Computer industry Biomedical engineering
Content Type	Text
Resource Type	Article

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