Fuzzy Modeling for Modifying Standard Prescriptions of Oriental Traditional Medicine
Nguyen Hoang Phuong*, Pratit Santiprabhob**, and Kaoru Hirota***
*Institute of Information Technology, National Center of Natural Science and Technology, 18 Hoang Quoc Viet Rd, Cau Giay Dist., Hanoi, Vietnam
**Department of Computer Science, University of Assumption University, Ramkhanghaeng Soi 24, Huamark, Bangkok 10240, Thailand
***Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama 226-8502, Japan
The aim of our research is to simulate a thinking of Traditional medical practitioners in forming a prescription of Oriental traditional medicine based on the observed symptoms of the patient. In this paper, we focus on modeling for modifying standard prescriptions of oriental Traditional medicine using the fuzzy sets theory when the standard prescription is given. Input data are symptoms and patient status which are represented as fuzzy sets and outputs are new ingredients of herbal plants of the given standard prescription and some new herbal plants constituting a advised prescription.