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Applying Fuzzy Logic and Neural Network to Rheumatism Treatment in Oriental Medicine
Author(s) -
Thang Cao,
Eric W. Cooper,
Yukinobu Hoshino,
Katsuari Kamei
Publication year - 2007
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2007.p0004
Subject(s) - medical prescription , medical diagnosis , artificial neural network , fuzzy logic , computer science , adaptive neuro fuzzy inference system , artificial intelligence , machine learning , rheumatism , inference , decision support system , fuzzy inference , medicine , fuzzy control system , data mining , pathology , nursing
In this paper, we present an application of soft computing into a decision support system RETS: Rheumatic Evaluation and Treatment System in Oriental Medicine (OM). Inputs of the system are severities of observed symptoms on patients and outputs are a diagnosis of rheumatic states, its explanations and herbal prescriptions. First, an outline of the proposed decision support system is described after considering rheumatic diagnoses and prescriptions by OM doctors. Next, diagnosis by fuzzy inference and prescription by neural networks are described. By fuzzy inference, RETS diagnoses the most appropriate rheumatic state in which the patient appears to be infected, then it gives a prescription written in suitable herbs with reasonable amounts based on neural networks. Training data for the neural networks is collected from experienced OM physicians and OM text books. Finally, we describe evaluations and restrictions of RETS.

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