Diagnosis based on decision tree and discrimination analysis for chronic hepatitis b in TCM

Abstract

Accurate discriminants of relationship between syndromes and syndrome information (symptoms, and lab indicators) are much desired in medical diagnosis applications. Although discriminants have been applied widely, the researches and applications of discriminant diagnosis model (DDT) are still blanks in diagnosis of chronic hepatitis B in traditional Chinese medicine (TCM). In this paper, a new discriminant diagnosis model constructed by attribute selection, decision tree C5.0 algorithm and discrimination analysis is proposed, which consists of two phases. One is attribute selection. The critical attributes are filtered out from the original attributes. The other is modeling phase to acquire discriminants between syndromes of chronic hepatitis B and syndrome information in TCM. From our experiments, combinations of TCM clinical symptoms and lab indicators are selected to provide formulas for syndrome differentiation of chronic hepatitis B in TCM from original 247 symptoms initially, and the model shows a better prospect for application in TCM diagnosis.