Identifying Association Rules among Drugs in Prescription of a Single Drugstore Using Apriori Method

Ahmad Yoosofan; Fatemeh Ghovanlooy Ghajar; Sima Ayat; Somayeh Hamidi; Farshad Mahini

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Identifying Association Rules among Drugs in Prescription of a Single Drugstore Using Apriori Method

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These days, health care systems such as pharmacies and drugstores normally produce high volumes of data. Consequently, utilizing data mining methods in health care systems has become a conventional process. In this research, Apriori algorithm has been applied to perform data mining using the data obtained from the prescriptions ordered within a pharmacy. Ten association rules were achieved from the assigned pharmaceutical drugs in those prescriptions using the aforementioned Apriori algorithm. The accuracy of these rules is also manually studied and reviewed by a physician. Among these association rules, Vitamin D and Calcium pills are the most interrelated medications, and Omeprazole and Metronidazole rankd second in terms of association. The results of this study provide useful feedback information about associations among drugs.

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来源
《智能信息管理（英文）》 |2015年第5期|253-259|共7页
作者
Ahmad Yoosofan; Fatemeh Ghovanlooy Ghajar; Sima Ayat; Somayeh Hamidi; Farshad Mahini;
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作者单位

Electrical and Computer Engineering Department;

University of Kashan;

Kashan;

Iran;

Electrical and Computer Engineering Department;

Isfahan University of Technology;

Isfahan;

Iran;

Department of Mechanical Engineering;

Villanova University;

Villanova;

PA;

USA;

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原文格式 PDF
正文语种 chi
中图分类肿瘤学;
关键词
Data; Mining; Association; Rules; Purchase; Portfolio; Analysis; Apriori;

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Identifying Association Rules among Drugs in Prescription of a Single Drugstore Using Apriori Method

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