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

  • Hoang Phuong NguyenEmail author
  • Lam Tung Vu
  • Thuy Hong Truong
  • Kaoru Hirota
Chapter
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Part of the Studies in Computational Intelligence book series (SCI, volume 899)

Abstract

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.

Keywords

Fuzzy expert systems Traditional Vietnamese Medicine Syndrome diagnosis 

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  • Hoang Phuong Nguyen
    • 1
    Email author
  • Lam Tung Vu
    • 2
  • Thuy Hong Truong
    • 3
  • Kaoru Hirota
    • 4
  1. 1.Thang Long UniversityHanoiVietnam
  2. 2.Nam Dinh University of Technical PedalogyNam ĐịnhVietnam
  3. 3.Thai Nguyen University of Medicine and PharmacyThái NguyênVietnam
  4. 4.Beijing Institute of TechnologyBeijingChina

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