Combination of K-Means and Profile Matching for Drag Substitution

S. Paembonan, Abdul Rachman Manga’, Jusmidah, Dedy Atmajaya, Ayu Vina Waluyantari, Wistiani Astuti, St. Hajrah Mansyur
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引用次数: 3

Abstract

Substitution of medicines can be done when the medicine required by a patient in the pharmacy is exhausted. In substituting prescription medicines, the pharmacist must notify patients that medicine substitution contains same active ingredients in equal amounts, same type, and its price is different. The right of medicine substitution belongs to pharmacists as long as the doctor allows the substitution. This method serves to make some similar medicines into a particular data set. This researched used K-means method. In terms of time, this method can be used to reduce the searching time process of medicines required by patients. Selection profile matching method was used to determine the medicine substitute recommendations based on the most ideal medicines selection for patients. The recommended medicine’s substances were exactly the same as the previous medicines listed in the prescription. Evaluation clustering used elbow method with cluster k = 3. Based on the experiments, the recommendation of medicine substitution with K-means and profile matching produced accuracy was 0.93506.
结合k -均值和轮廓匹配进行阻力替换
当药房中病人所需的药物用尽时,可以进行药物替代。药师替代处方药,必须告知患者替代药品含有相同有效成分、相同数量、相同种类、不同价格。在医生允许的情况下,药品替代权属于药师。这种方法用于将一些类似的药物放入特定的数据集。本研究采用K-means方法。在时间上,该方法可以减少患者所需药物的搜索时间过程。采用选择概况匹配法,根据患者最理想的药物选择,确定替代药物推荐方案。推荐的药物的物质与处方上列出的以前的药物完全相同。评价聚类采用肘部法,聚类k = 3。通过实验,采用K-means和剖面匹配推荐替代药物的准确率为0.93506。
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