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

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Part of the book series: Studies in Computational Intelligence ((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.

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Correspondence to Hoang Phuong Nguyen .

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Nguyen, H.P., Vu, L.T., Truong, T.H., Hirota, K. (2021). ESYNDIAG: A Fuzzy Expert System for Eight Syndrome Diagnosis in Traditional Vietnamese Medicine. In: Kreinovich, V., Hoang Phuong, N. (eds) Soft Computing for Biomedical Applications and Related Topics. Studies in Computational Intelligence, vol 899. Springer, Cham. https://doi.org/10.1007/978-3-030-49536-7_12

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