Application of Data Mining in Diagnose of Traditional Chinese Medicine-A Case Study on the Rheumatism Arthritis
Data mining technology is an important method to analyze the medical cases. However, how do we choose the appropriate indexes to make the TCM more scientific? How do we improve the diagnosis and treatment level of doctors? Moreover, how do we supervise the quality more effectively? In view of this problem, this paper brings forward a new medical indexes reduction method-the Bayesian network based on clustering. Through classify the data to pick-up the main characters and species characters to research traditional Chinese medicine symptomatology type and dynamic evolvement, and it provide the important research evidence to RA pathogens and sickness mechanism. Moreover, it supervises diagnosis quality of the clinician. We also exploit the medical quality complete supervision system ( MQCSS), now the system has already generalized in some hospitals such as Taiyuan Rheumatism hospital and has good effects.
Data Mining Clustering Bayesian Network Traditional Chinese Medicine (TCM)
Fan Jianping
School of Management, Shanxi University, Taiyuan P.R.China, 030006
国际会议
天津
英文
2007-10-20（万方平台首次上网日期，不代表论文的发表时间）