Traditional Chinese medicine (TCM) is one of the safe and effective methods to treat liver cir-rhosis. The practitioners of TCM assess hepatic function in term of syndrome. But the course of syndrome differentiation i...Traditional Chinese medicine (TCM) is one of the safe and effective methods to treat liver cir-rhosis. The practitioners of TCM assess hepatic function in term of syndrome. But the course of syndrome differentiation is subjectivity. At pre-sent most of all the researches are focused on the relationship between the syndrome and the Western medicine objective indicators such as child-pugh grade. In fact syndrome is the syn-thesis of signs and symptoms and collecting signs, symptoms is easy than syndrome differ-entiation. We try to explore the relationship be-tween the objective Western medicine standard such as child-pugh grade, decompensation or compensation stage, active or inactive period and the signs and symptoms of TCM by using the data mining method. We use the information gain method to assess the attributes and use five typical classifiers such as logistic, Bayes-Net, NaiveBayes, RBF and C4.5 to obtain the classification accuracy. After attribute selection, we obtain the main symptoms and signs of TCM relating to the stage, period and child-pugh grade about liver cirrhosis. The experiment re-sults show the classification accuracy is im-proved after filtering some symptoms and signs.展开更多
文摘Traditional Chinese medicine (TCM) is one of the safe and effective methods to treat liver cir-rhosis. The practitioners of TCM assess hepatic function in term of syndrome. But the course of syndrome differentiation is subjectivity. At pre-sent most of all the researches are focused on the relationship between the syndrome and the Western medicine objective indicators such as child-pugh grade. In fact syndrome is the syn-thesis of signs and symptoms and collecting signs, symptoms is easy than syndrome differ-entiation. We try to explore the relationship be-tween the objective Western medicine standard such as child-pugh grade, decompensation or compensation stage, active or inactive period and the signs and symptoms of TCM by using the data mining method. We use the information gain method to assess the attributes and use five typical classifiers such as logistic, Bayes-Net, NaiveBayes, RBF and C4.5 to obtain the classification accuracy. After attribute selection, we obtain the main symptoms and signs of TCM relating to the stage, period and child-pugh grade about liver cirrhosis. The experiment re-sults show the classification accuracy is im-proved after filtering some symptoms and signs.
