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

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 Slasis and heat smoldering syndrome. Thus the decision tree classification model is obtained and some important factors are selected to three mainly syndromes of posthepatilic 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.