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JACIII Vol.24 No.5 pp. 656-661
doi: 10.20965/jaciii.2020.p0656
(2020)

Paper:

Building a Fuzzy System for Pulse Based Disease Diagnosis and Acupuncture Therapy

Hoang Phuong Nguyen*,† and Truong Thi Hong Thuy**

*Division Informatics, Math-Informatics Faculty, Thanglong University
Nghiem Xuan Yem Road Hoang Mai District, Hanoi, Vietnam

**Thai Nguyen University of Medicine and Pharmacy
Thai Nguyen Province, Vietnam

Corresponding author

Received:
March 25, 2020
Accepted:
May 24, 2020
Published:
September 20, 2020
Keywords:
pulse-based diagnosis, expert systems, acupuncture therapy, fuzzy logic, traditional medicine
Abstract

Pulse-based disease diagnosis and acupuncture therapy are the key components of traditional Oriental medicine. This study aims to model the thinking of medical doctors with regard to their use of pulse-based diagnosis and acupuncture therapy. This paper focuses on a fuzzy inference and knowledge base, which are the main components of the system for pulse based disease diagnosis and acupuncture therapy. The input of the system is the pulse symptoms of the patient with fuzzy degrees, whereas the output is the disease diagnosis and acupuncture therapy prescription. In this system, the knowledge base consists of nearly 1,200 rules for diagnosis and treatment. An evaluation of a group of traditional medical doctors indicates that the results of the newly proposed system are in good accordance with those of doctors practicing traditional medicine. This approach leads to better results than previous approaches because it uses fuzzy logic, which is an appropriate tool here because most entities in traditional medicine are fuzzy in nature. The system of pulse-based disease diagnosis and acupuncture therapy can mimic the thinking of traditional practitioners, and it can be a “good teacher” for medical students who want to learn traditional Vietnamese medicine.

Cite this article as:
H. Nguyen and T. Thuy, “Building a Fuzzy System for Pulse Based Disease Diagnosis and Acupuncture Therapy,” J. Adv. Comput. Intell. Intell. Inform., Vol.24, No.5, pp. 656-661, 2020.
Data files:
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Last updated on Dec. 01, 2020