教師資料查詢 | 類別: 期刊論文 | 教師: 陳俊豪 CHUN-HAO CHEN (瀏覽個人網頁)

標題:Hybrid data mining approaches for prevention of drug dispensing errors
學年98
學期2
出版(發表)日期2010/06/01
作品名稱Hybrid data mining approaches for prevention of drug dispensing errors
作品名稱(其他語言)
著者Chen, Lien-Chin; Chen, Chun-Hao; Chen, Hsiao-Ming; Tseng, Vincent S.
單位淡江大學資訊工程學系
出版者New York: Springer New York LLC
著錄名稱、卷期、頁數Journal of Intelligent Information Systems 36(3), pp.305-327
摘要Prevention of drug dispensing errors is an importance topic in medical care. In this paper, we propose a risk management approach, namely Hybrid Data Mining (HDM), to prevent the problem of drug dispensing errors. An intelligent drug dispensing errors prevention system based on the proposed approach is then implemented. The proposed approach consists of two main procedures: First, the classification modeling and logistic regression approaches are used to derive decision tree and regression function from the given dispensing errors cases and drug databases. In the second procedure, similar drugs are then gathered together into clusters by combing clustering technique (PoCluster) and the extracted logistic regression function. The drugs that may cause dispensing errors will then be alerted through the clustering results and the decision tree. Through experimental evaluation on real datasets in a medical center, the proposed approach was shown to be capable of discovering the potential dispensing errors effectively. Hence, the proposed approach and implemented system serve as very useful application of data mining techniques for risk management in healthcare fields.
關鍵字Dispensing errors; Classification modeling; Decision tree; Logistic regression; Medical risk management
語言英文
ISSN0925-9902; 1573-7675
期刊性質國外
收錄於SCI
產學合作
通訊作者
審稿制度
國別荷蘭
公開徵稿
出版型式紙本
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