Earticle

초록

영어

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.

목차

Abstract
 1. Introduction
 2. Preparing Database
  2.1. Data Collection
  2.2. Database Entity Structure
 3. Disease Classification System with Fuzzy ART and Fuzzy Inference Algorithm
 4. Experiment and Analysis
 5. Conclusions
 References

키워드

저자

• Kwang Baek Kim [ Department of Computer Engineering, Silla University, Busan 617-736, Korea ] Corresponding Author
• Doo Heon Song [ Department of Computer Games, Songdam College, Yongin 449-040, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605