TY - GEN
T1 - Decision tree method to extract syndrome differentiation rules of posthepatitic cirrhosis in traditional Chinese medicine
AU - Wang, Yan
AU - Ma, Lizhuang
AU - Liao, Xiaowei
AU - Liu, Ping
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/62949136005
U2 - 10.1109/ITME.2008.4743965
DO - 10.1109/ITME.2008.4743965
M3 - 会议稿件
AN - SCOPUS:62949136005
SN - 9781424423262
T3 - Proceedings of 2008 IEEE International Symposium on IT in Medicine and Education, ITME 2008
SP - 744
EP - 748
BT - Proceedings of 2008 IEEE International Symposium on IT in Medicine and Education, ITME 2008
T2 - 2008 IEEE International Symposium on IT in Medicine and Education, ITME 2008
Y2 - 12 December 2008 through 14 December 2008
ER -