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퍼지 의사 결정 트리를 이용한 한의학 기반의 건강 사전 진단 시스템

Oriental Medicine-based Health Pre-Diagnosis System using Fuzzy Decision Tree

  • Kim, Kwang Baek (Department of Artificial Intelligence, Silla University)
  • 투고 : 2021.09.27
  • 심사 : 2021.10.02
  • 발행 : 2021.11.30

초록

본 논문에서는 퍼지 의사 결정 트리를 이용한 한의학 기반의 건강 사전 진단 시스템을 제안한다. 제안된 퍼지 의사결정 트리 기반 한방 사전 진단 방법은 과거의 데이터를 미리 학습시킨 후에 엔트로피에 따라 경계 값을 계산한 후, 사용자가 여러 증상을 선택하면 선택된 증상에 해당되는 상위 질병 5개를 도출한다. 그리고 도출된 상위 5개의 질병과 도출된 질병의 원인과 민간요법을 제공한다. 질병과 증상에 대한 데이터베이스는 한의사가 추천한 여러 한의학 전문 서적을 기반으로 증상과 질병의 데이터베이스를 설계하고 한의학 전문의가 검증한 후에 구현하였다. 과거의 데이터를 바탕으로 증상을 학습함으로써 제안된 한의학 기반 건강 사전 진단 시스템 방법은 보다 정확한 진단 결과를 더 빨리 제공할 수 있다.

In this paper, we propose a method that uses fuzzy decision tree based health pre-diagnosis system of oriental medicine. The proposed fuzzy decision tree based health pre-diagnosis system uses the data from the past which has been pre-trained to get the boundary values based on entropy then, when the user inputs the symptoms, the top 5 diseases that causes those symptoms are extracted. With the extracted top 5 diseases, the system provides information on those diseases with the cause and how to treat them with folk remedies. The database of the diseases and their symptoms is established with the information based on the various books that the oriental doctor recommended then reviewed by the oriental doctor for confirmation. By utilizing the data from the past to train the symptoms of the diseases, the proposed oriental medicine-based health pre-diagnosis system method could provide more accurate diagnosis results faster.

키워드

참고문헌

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