Journal of Biomedical Engineering Research (대한의용생체공학회:의공학회지)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
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Rule Weight-Based Fuzzy Classification Model for Analyzing Admission-Discharge of Dyspnea Patients

호흡곤란환자의 입-퇴원 분석을 위한 규칙가중치 기반 퍼지 분류모델

  • Son, Chang-Sik (Biomedical Informatics Technology Center, Keimyung Univ.) ;
  • Shin, A-Mi (Dept. of Medical Informatics, School of Medicine, Keimyung Univ.) ;
  • Lee, Young-Dong (Biomedical Informatics Technology Center, Keimyung Univ.) ;
  • Park, Hyoung-Seob (Interventional Cardiology Dept. of Internal Medicine, Keimyung Univ.) ;
  • Park, Hee-Joon (Dept. of Medical Informatics, School of Medicine, Keimyung Univ.) ;
  • Kim, Yoon-Nyun (Interventional Cardiology Dept. of Internal Medicine, Keimyung Univ.)
  • 손창식 (계명대학교 생체정보기술개발사업단) ;
  • 신아미 (계명대학교 의과대학 의료정보학교실) ;
  • 이영동 (계명대학교 생체정보기술개발사업단) ;
  • 박형섭 (계명대학교 동산병원 심장내과) ;
  • 박희준 (계명대학교 의과대학 의료정보학교실) ;
  • 김윤년 (계명대학교 동산병원 심장내과)
  • Received : 2009.08.03
  • Accepted : 2010.02.19
  • Published : 2010.02.28
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Abstract

A rule weight -based fuzzy classification model is proposed to analyze the patterns of admission-discharge of patients as a previous research for differential diagnosis of dyspnea. The proposed model is automatically generated from a labeled data set, supervised learning strategy, using three procedure methodology: i) select fuzzy partition regions from spatial distribution of data; ii) generate fuzzy membership functions from the selected partition regions; and iii) extract a set of candidate rules and resolve a conflict problem among the candidate rules. The effectiveness of the proposed fuzzy classification model was demonstrated by comparing the experimental results for the dyspnea patients' data set with 11 features selected from 55 features by clinicians with those obtained using the conventional classification methods, such as standard fuzzy classifier without rule weights, C4.5, QDA, kNN, and SVMs.

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