CAJ | 학술논문

提出通过建立疾病字符库的字符串比对算法来解决早期数据录入不规范的问题。通过设置Apriori算法的最小关联度和置信度，对急诊内科病例数据进行数据采集、预处理和关联挖掘，揭示各类急性发作疾病潜在的关联规则。研究结果可为急诊医生提供决策支持，为治疗争取时间。
제출통과건립질병자부고적자부천비대산법래해결조기수거록입불규범적문제。통과설치Apriori산법적최소관련도화치신도，대급진내과병례수거진행수거채집、예처리화관련알굴，게시각류급성발작질병잠재적관련규칙。연구결과가위급진의생제공결책지지，위치료쟁취시간。
In order to solve the problem of data nonstandard input, this paper put forward a string matching method based on disease character library. Through setting the minimum correlation degree and minimum confidence level, the method collected, pretreated and mined the emergency internal case data, then revealed the potential association rules for all kinds of acute diseases. Those provide decision support for diagnosis and give aid to curative time.