Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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A CAOPI System Based on APACHE II for Predicting the Degree of Severity of Emergency Patients

응급환자의 중증도 예측을 위한 APACHE II 기반 CAOPI 시스템

  • Lee, Young-Ho (u-healthcare Institute, Gachon University of Medicine and Science) ;
  • Kang, Un-Gu (u-healthcare Institute, Gachon University of Medicine and Science) ;
  • Jung, Eun-Young (u-Healthcare Center, Gachon University Gil Hospital) ;
  • Yoon, Eun-Sil (u-healthcare Institute, Gachon University of Medicine and Science) ;
  • Park, Dong-Kyun (u-Healthcare Center, Gachon University Gil Hospital)
  • 이영호 (가천의과학대학교 유헬스케어연구소) ;
  • 강운구 (가천의과학대학교 유헬스케어연구소) ;
  • 정은영 (가천의대 길병원 유헬스케어센터) ;
  • 윤은실 (가천의과학대학교 유헬스케어연구소) ;
  • 박동균 (가천의대 길병원 유헬스케어센터)
  • Received : 2010.10.14
  • Accepted : 2010.11.01
  • Published : 2011.01.31
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Abstract

This study proposes CAOPI(Computer Aided Organ Prediction Index) system based on APACHE II(Acute Physiology And Chronic Health Evaluation) for classifying disease severity and predicting the conditions of patients' major organs. The existing ICU disease severity evaluation is mostly about calculating risk scores using patients' data at certain points, which has limitations on making precise treatments. CAOPI system is designed to provide personalized treatments by classifying accurate severity degrees of emergency patients, predicting patients' mortality rate and scoring the conditions of certain organs.

본 연구에서는 환자의 중증도 분류 및 인체 주요 장기의 상태 예측을 위하여 APACHE II(Acute Physiology And Chronic Health Evaluation) 기반 CDSS 도구인 CAOPI(Computer Aided Organ Prediction Index) 시스템을 제안한다. 기존 ICU 환자의 중증도 평가방법은 APACHE II를 이용하여 특정 시점의 중환자 위험도를 특정한 시점 데이터를 이용하여 산출하는 방식이었으나, 실시간으로 변화하는 환자의 상태에 맞춰 조치를 취하는데는 한계가 있다. CAOPI 시스템은 중환자실에 입실하는 환자들의 질병 중증도를 정확히 분류하고, 환자의 사망예측 뿐만 아니라장기 상태를 시각화 하여 위험도를 수치화 하였다. 또한 위험도를 특정 장기별로 구분하여 담당의 사가 환자의 상태에 맞는 맞춤형 응급조치를 취할 수 있도록 설계 및 개발 하였다.

Keywords

References

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