Decision Tree Method to Extract Syndrome Differentiation Rules of Posthepatitic Cirrhosis in Traditional Chinese Medicine

摘要：

Syndrome differentiation is an important topic in traditional Chinese medicine (TCM). Decision tree, one of the data mining algorithms developed, is a method to induce rules from data. In this paper,decision tree is applied to extract syndrome differentiation rules from 293 cases related to liver and kidney yin deficiency, damp-heat smoldering and Stasis and heat smoldering syndrome. Thus the decision tree classification model is obtained and some important factors are selected to three mainly syndromes of posthepatitic cirrhosis; corresponding syndrome differentiation rules are induced from the model. The classification accuracies are 79.86％, 80. 5％ and 82％respectively. The experiment results show that the decision method is likely a promising method to extract diagnostic rules from patient records of Chinese medicine and could be expected to be useful in the practice of traditional Chinese medicine.

作者: WANG Yan MA Lizhuang LIAO Xiaowei LIU Ping

作者单位: Department of Computer Science & Engineering,Shanghai Jiao tong University,Shanghai 200240,China Department of Computer Science & Engineering,Shanghai Jiao tong University,Shanghai 200240,China;Cen Institute of Liver Diseases,Shanghai University of Traditional Chinese Medicine,Shanghai 201203,Chin

会议类型: 国际会议

会议名称: 2008 IEEE International Symposium on IT in Medicine and Education(2008信息技术在医学和教育中的应用国际研讨会)(ITME 2008)

会议地点: 厦门

会议语种:英文

页码: 744-748

在线出版日期: 2008-12-12（万方平台首次上网日期，不代表论文的发表时间）