title: Discovering treatment pattern in Traditional Chinese Medicine clinical cases by exploiting supervised topic model and domain knowledge.
abstract: In Traditional Chinese Medicine (TCM), the prescription is the crystallization of clinical experience of doctors, which is the main way to cure diseases in China for thousands of years. Clinical cases, on the other hand, describe how doctors diagnose and prescribe. In this paper, we propose a framework which mines treatment patterns in TCM clinical cases by exploiting supervised topic model and TCM domain knowledge. The framework can reflect principle rules in TCM and improve function prediction of a new prescription. We evaluate our method on 3090 real world TCM clinical cases. The experiment validates the effectiveness of our method.
authors.affiliation: College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China. Electronic address: yaoliang@zju.edu.cn.
authors.forename: Liang
authors.initials: L
authors.lastname: Yao
authors.affiliation: College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China. Electronic address: yinzh@zju.edu.cn.
authors.forename: Yin
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China. Electronic address: wbg@zju.edu.cn.
authors.forename: Baogang
authors.initials: B
authors.lastname: Wei
authors.affiliation: College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China. Electronic address: stephenwangw@163.com.
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
authors.affiliation: College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China. Electronic address: yjzhangshi@163.com.
authors.forename: Yuejiao
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China. Electronic address: xiaolinr@126.com.
authors.forename: Xiaolin
authors.initials: X
authors.lastname: Ren
authors.affiliation: College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China. Electronic address: bianyali@zju.edu.cn.
authors.forename: Yali
authors.initials: Y
authors.lastname: Bian
mesh_terms: D008516:Medicine, Chinese Traditional; D008962:Models, Theoretical
keywords: Clinical cases; TCM domain knowledge; Topic model; Traditional Chinese Medicine; Treatment pattern discovery