A decision support system for rheumatic evaluation and treatment in oriental medicine using fuzzy logic and neural network

  • Authors:

  • Cao Thang;Eric W. Cooper;Yukinobu Hoshino;Katsuari Kamei

  • Affiliations:

  • Graduate School of Science and Engineering, Ritsumeikan University, Japan;21st Century Center of Excellence, Ritsumeikan University, Japan;College of Information Science and Engineering, Ritsumeikan University, Japan;College of Information Science and Engineering, Ritsumeikan University, Japan

  • Venue:
  • MDAI'05 Proceedings of the Second international conference on Modeling Decisions for Artificial Intelligence
  • Year:
  • 2005

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Abstract

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 an oriental 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.