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Decision tree method to extract syndrome differentiation rules of posthepatitic cirrhosis in traditional Chinese medicine

机译:决策树法提取肝硬化后中医辨证规律

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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.
机译:辨证是中医研究的重要课题。决策树是数据挖掘算法之一,是一种从数据中推导规则的方法。本文应用决策树从293例肝肾阴虚,湿热阴虚,瘀阴热阴虚证中提取辨证规则。从而获得了决策树分类模型,并针对肝炎后肝硬化的三种主要证候选择了一些重要的因素。从模型中得出相应的证候区分规则。分类准确度分别为79.86%,80.5%和82%。实验结果表明,该决策方法可能是从中医病历中提取诊断规则的一种有前途的方法,有望在中医实践中有用。

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