• Title/Summary/Keyword: Self-diagnosing Disease Classification System

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Self-Diagnosing Disease Classification System for Oriental Medical Science with Refined Fuzzy ART Algorithm (Refined Fuzzy ART 알고리즘을 이용한 한방 자가 질병 분류 시스템)

  • Kim, Kwang-Baek
    • The Journal of the Korea Contents Association
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    • v.9 no.7
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    • pp.1-8
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    • 2009
  • In this paper, we propose a home medical system that integrates a self-diagnosing disease classification system and a tele-consulting system by communication technology. The proposed disease classification system supports to self-diagnose the health condition based on oriental medical science using fuzzy neural network algorithm. The prepared database includes 72 different diseases and their associated symptoms based on a famous medical science book "Dong-eui-bo-gam". The proposed system extracts three most prospective diseases from user's symptoms by analyzing disease database with fuzzy neural network technology. Technically, user's symptoms are used as an input vector and the clustering algorithm based upon a fuzzy neural network is performed. The degree of fuzzy membership is computed for each probable cluster and the system infers the three most prospective diseases with their degree of membership. Such information should be sent to medical doctors via our tele-consulting system module. Finally a user can take an appropriate consultation via video images by a medical doctor. Oriental medical doctors verified the accuracy of disease diagnosing ability and the efficacy of overall system's plausibility in the real world.