计算机工程与应用2016，Vol.52Issue(18)：8-13,6.DOI:10.3778/j.issn.1002-8331.1603-0114
MaLDA：基于LDA的用药分析
MaLDA:medication analysis based on LDA
摘要
Abstract
To provide support for doctors and patients to use drugs in a safer, more rational and efficient way, this paper proposes a framework for medication analysis based on LDA(Latent Dirichlet Allocation), MaLDA(Medication Analysis based on the LDA). MaLDA combines the usage of medication records and diagnostic records, infers the function of each drug using topic-based inference model LDA, which regards a drug as a document, a function as a topic, and a disease as a word. As a result, related drugs, drug and disease, related diseases are associated by functions. Then clustering all drugs according to its distribution of functions, and each cluster is described by related diseases. Finally, it analyzes the clinical medication based on the results of clustering. The result generated by MaLDA can not only find the drug which is better in treatment, but also find the drug combination which lays the foundation for mining drug side effects and the complications of disease. The method is evaluated by using 137 510 patients’diagnostic records and medication records. The results justify the advantages of MaLDA over baseline methods on medication analysis.关键词
数据挖掘/用药分析/主题模型/隐含的狄利克雷分布Key words
data mining/medication analysis/topic model/Latent Dirichlet Allocation(LDA)分类
信息技术与安全科学引用本文复制引用
周靖,佘玉轩,熊赟..MaLDA：基于LDA的用药分析[J].计算机工程与应用,2016,52(18):8-13,6.基金项目
国家高技术研究发展计划（863）（No.2015AA020105）；国家自然科学基金（No.91546105，No.71331005）；上海市科委基金（No.14511107302）；上海市数据科学重点实验室开放课题资助课题（No.201509060001）；NSFC-广东联合基金（第二期）超级计算科学应用研究专项资助；国家超级计算广州中心支持。 （）
