Developing an Intelligent Health Pre-diagnosis System for Korean Traditional Medicine Public User

Korea Traditional Medicine is popular in use among Korean public but there exist few available health information systems on the internet. A computerized self-checking diagnosis system is proposed to reduce the social cost by monitoring health status with simple symptom checking procedures especially for Korea Traditional Medicine users. Methods: Based on the national reports for disease/symptoms of Korea Traditional Medicine, we build a reliable database and devise an intelligent inference engine using Fuzzy ART Clustering. The implemented system gives five most probable diseases a user might have with respect to symptoms given by the user. Thus, in this paper, we propose a self-diagnosis system of Korean traditional medicine based on Korean Standard Causes of Death Disease Classification Index(KCD) and Fuzzy ART/inference method. Since this is for self-diagnosis, our system has graphical user-friendly interface that accepts symptoms of user from a certain part of body where the user feels inconvenient. Inference results are verified by Korea Traditional Medicine doctors as sufficiently accurate and easy to use.