Applying Fuzzy Logic and Neural Network to Rheumatism Treatment in Oriental Medicine

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 a 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.

[1]  Michael Negnevitsky,et al.  Artificial Intelligence: A Guide to Intelligent Systems , 2001 .

[2]  E.W. Cooper,et al.  Townscape Color Planning System Using an Evolutionary Algorithm and Kansei Evaluations , 2006, 2006 IEEE International Conference on Fuzzy Systems.

[3]  Jeremy Wyatt,et al.  Clinical applications of artificial neural networks: Artificial neural networks: practical considerations for clinical application , 2001 .

[4]  Rashmi Pandya.  Expert systems: design and development, and Expert systems catalog of applications, by John Durkin. Prentice Hall International , 1999, Knowl. Eng. Rev..

[5]  L. Gierl,et al.  Adaptation and abstraction as steps towards case-based reasoning in the real medical world: case-based selection strategies for antibiotics therapy. , 1995, Medinfo. MEDINFO.

[6]  Eric W. Cooper,et al.  Modeling Designers' Color Decision Processes Through Emotive Choice Mapping , 2005, MDAI.

[7]  Ramón López de Mántaras,et al.  RENOIR: An expert system using fuzzy logic for rheumatology diagnosis , 1994, Int. J. Intell. Syst..

[8]  Katsuari Kamei,et al.  An Application of FEERL (Fuzzy Environment Evaluation Reinforcement Learning) to LightsOut Game and Avoidance of Detour Actions in Search , 2001 .

[9]  P H Bartels,et al.  Atypical adenomatous hyperplasia (adenosis) of the prostate: development of a Bayesian belief network for its distinction from well-differentiated adenocarcinoma. , 1996, Human pathology.

[10]  Yukinobu Hoshino,et al.  A Decision Support System for Rheumatic Evaluation and Treatment in Oriental Medicine Using Fuzzy Logic and Neural Network , 2005, MDAI.

[11]  Hoang-Phuong Nguyen.  Approximate reasoning for oriental traditional medical expert systems , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[12]  K Guo,et al.  FUZZY SET MODEL AND COMPUTERIZED DIAGNOSIS SYSTEM IN TRADITIONAL CHINESE MEDICINE , 1981 .

[13]  Kaoru Hirota,et al.  Fuzzy Modeling for Modifying Standard Prescriptions of Oriental Traditional Medicine , 2003, J. Adv. Comput. Intell. Intell. Informatics.

[14]  Yukinobu Hoshino,et al.  A Proposal of Reinforcement Learning with Fuzzy Environment Evaluation Rules and Its Application to Chess , 2001 .

[15]  Yukinobu Hoshino,et al.  A Fuzzy Clustering Based Selection Method to Maintain Diversity in Genetic Algorithms , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[16]  Ario Ohsato,et al.  Developing Case-based Reasoning System for Medical Consultation Using the Importance of Features , 2002, J. Adv. Comput. Intell. Intell. Informatics.

[17]  Anastasios Bezerianos,et al.  Radial basis function neural networks for the characterization of heart rate variability dynamics , 1999, Artif. Intell. Medicine.

[18]  Maysam F. Abbod,et al.  Survey of utilisation of fuzzy technology in Medicine and Healthcare , 2001, Fuzzy Sets Syst..

[19]  K Boegl,et al.  [New approaches to computer-assisted diagnosis of rheumatologic diseases]. , 1995, Der Radiologe.

[20]  Edward H. Shortliffe,et al.  Computer-based medical consultations, MYCIN , 1976 .

[21]  R. Dybowski,et al.  Comprar Clinical Applications of Artificial Neural Networks | Richard Dybowski | 9780521001335 | Cambridge University Press , 2007 .