The recommendation of medicines based on multiple criteria decision making and domain ontology — An example of anti-diabetic medicines

R. Chen, Jiun Yao Chiu, Cho Tsan Batj
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引用次数: 20

Abstract

A recommendation system can help user to make requirement analysis and to recommend better decision from much complex information. This research is concentrated on medical prescription recommendation. According to the statistics of Department of Health, diabetes was the top ten of death in Taiwan. Therefore, developing an effective treatment for diabetes is very important. The purpose of this study is to develop a decision support system to assist a doctor to make more appropriate decision in selecting drugs. We first built the ontology of diabetic knowledge and compute medication by multiples criteria decision making method (MCDM). The entropy was used to compute data of patient's history and then take this result to integrate medicine knowledge ontology to list appropriate medications. Finally, more suitable medications are recommended to doctors. Primary experiments proof our method is useful.
基于多标准决策和领域本体的药物推荐——以抗糖尿病药物为例
推荐系统可以帮助用户从大量复杂的信息中进行需求分析,并给出更好的决策建议。本研究的重点是医疗处方推荐。根据卫生署统计,糖尿病是台湾十大死亡原因之一。因此,开发一种有效的治疗糖尿病的方法是非常重要的。本研究的目的是开发一个决策支持系统,以协助医生在选择药物时做出更合适的决策。首先建立糖尿病知识本体,采用多准则决策方法(MCDM)进行用药计算。利用熵值计算患者病史数据,并以此结果整合医学知识本体,列出合适的药物。最后,向医生推荐更合适的药物。初步实验证明我们的方法是有用的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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