의사결정 지원시스템을 위한 전자의무기록의 분류학습

배인호1), 김진상*1), 김윤년1)

1)계명대학교 정보통신대학 컴퓨터공학부

Abstract : We employed a hierarchical document classification method to classify a massive collection of electronic medical records(EMR) written in both Korean and English. Our experimental system has been learned from 5,000 records of EMR text data and predicted a newly given set of EMR text data over 68% correctly. We expect the accuracy rate can be improved greatly provided a dictionary of medical terms or a suitable medical thesaurus. The classification system might play a key role in some clinical decision support systems and various interpretation systems for clinical data.
keyword : Classification, electronic medical records, clinical decision support system, text mining

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