Using Topic Model for Intelligent Computer-Aided Diagnosis in Traditional Chinese Medicine

Abstract

This research work presents the use of Latent Dirchlet Allocation (LDA), a generative topic modeling technique to extract latent patterns in Chinese Traditional Medical (CTM) diagnose and treatment data. It can help to capture the relationship between symptom and diseases. The purpose of the research is to acquire proficient medical knowledge by computer which can aid doctors to determine diagnosis. Our work proposed the framework which utilizes LDA to discoicvery latent patterns in the symptoms of medical cases and set up computer-aided diagnosis system in TCM.