Feature selection and syndrome prediction for liver cirrhosis in traditional Chinese medicine
Computer Methods and Programs in Biomedicine
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Finding the relationship between the objective factors of Western Medicine and the signs or the symptoms of Traditional Chinese Medicine (TCM) is an important topic. Because the factors of Western Medicine can be evaluated objectively and the treatment way of TCM is more effectively to some diseases. In this paper, C4.5 algorithm, one of the Decision Tree, is used to analyze the relationship between Child-Pugh degree and four examinations of TCM based on liver cirrhosis. We hope to look for a method of Integrating Traditional Chinese and Western Medicine. When using our dataset, some rules are obtained and the accuracy of the grade of Child-Pugh classification is 85.67%, 64.97%, 77.94% according to Child-Pugh A, Child-Pugh B and Child-Pugh C. To test if the method is effective, we compare with other algorithms such as: Logistic, BayesNet, RBF NN, ID3 algorithm. It is demonstrated that C4.5 outperform ID3, Logistic, BayesNet, and RBF NN.