ESYNDIAG: A Fuzzy Expert System for Eight Syndrome Diagnosis in Traditional Vietnamese Medicine

Hoang Phuong Nguyen*, Lam Tung Vu, Thuy Hong Truong, Kaoru Hirota

*此作品的通讯作者

科研成果: 书/报告/会议事项章节章节同行评审

摘要

A fuzzy rule—based expert system ESYNDIAG is presented for eight syndrome diagnosis in Traditional Vietnamese Medicine combining positive and negative rules. After designing and building a suitable inference engine for this system, efforts have been committed to create effective knowledge base consisting of more 800 positive rules for confirmation of conclusion and of more 100 negative rules for exclusion of the same conclusion. How the rule base is constructed, managed and used are focussed on for diagnosis of eight syndromes in Traditional Vietnamese medicine such as Yin syndrome, Yang syndrome, Superficial syndrome, deep syndrome, Cold syndrome, Hot syndrome, Deficiency syndrome, Excess syndrome. The inference engine shows how to combine positive and negative rules. The first evaluation of ESYNDIAG is presented by the traditional medicine expert’s group in Vietnam and confirmed that ESYNDIAG diagnoses with a high accuracy.

源语言英语
主期刊名Studies in Computational Intelligence
出版商Springer
127-139
页数13
DOI
出版状态已出版 - 2021

出版系列

姓名Studies in Computational Intelligence
899
ISSN(印刷版)1860-949X
ISSN(电子版)1860-9503

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