Latent Semantic Diagnosis in Traditional Chinese Medicine

摘要：

　　Traditional Chinese Medicine (TCM) is the main route of disease control for ancient Chinese.Through thousands of yearsdevelopment and inheriting,TCM is the most influential traditional medical system which lasts the longest time and used by the largest population.However,the theory of TCM lacks objective and quantitative standards.In this paper,we propose a statistical diagnosis approach to find out the pathogenesises based on the latent semantic analysis of symptoms and the corresponding herbs.We assume that the latent pathogenesis is the inherent connection between symptoms and herbs within a medical case.Previous topic models mostly focus on single content documents,but medical cases have two different contents: symptoms and herbs.We therefore develop a novel muti-content model based on LDA.We used the proposed model to analysis two TCM domains amenorrhea and lung cancer.Experiment results illustrate that the pathogenesises found by our model correspond well with the theory of TCM and it provides a theoretical data-driven approach to establish diagnosis standards.

关键词： Latent semantic model Traditional Chinese Medicine Clustering

作者: Wendi Ji Ying Zhang Xiaoling Wang Yiping Zhou

作者单位: Shanghai Key Laboratory of Trustworthy Computing,Institute for Data Science and Engineering,East Chi Basic Medical College,Shanghai University of Traditional Chinese Medicine,Pudong,China

会议类型: 国际会议

会议名称: International Asia-Pacific Web Conference(第18届国际亚太互联网大会)

会议地点: 苏州

会议语种:英文

页码: 395-407

在线出版日期: 2016-09-23（万方平台首次上网日期，不代表论文的发表时间）