Title :
Methodology study of classification algorithm in TCM ZHENG diagnosis
Author_Institution :
Dept. of Comput. Sci. & Technol., Dalian Neusoft Inst. of Inf., Dalian, China
Abstract :
Study of traditional Chinese medicine (TCM) Zheng is a key to the research of TCM modernization, and the core is the classification and diagnostic criteria of Zheng. The purpose of this article is aimed to survey the usage of classification algorithms of data mining in TCM ZHENG researches, and comprehensively analyze the main features of algorithms and their applications, including discriminant analysis, cluster analysis, decision tree, rough set, neural network and Bayesian network. The appropriate classification algorithm should be chosen according to different research purpose. This survey provides a summary on the advance of computational approaches for ZHENG diagnosis in each section and will be useful for future knowledge discovery in this area.
Keywords :
belief networks; data mining; decision trees; medical diagnostic computing; neural nets; patient diagnosis; pattern classification; pattern clustering; rough set theory; Bayesian network; TCM Zheng diagnosis; classification algorithm; cluster analysis; data mining; decision tree; discriminant analysis; neural network; rough set theory; traditional Chinese medicine Zheng; Accuracy; Bayes methods; Classification algorithms; Data mining; Decision trees; Medical diagnostic imaging; Neural networks; ZHENG diagnosis; classification; data mining; traditioanl Chinese medicine;
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2014 IEEE International Conference on
Conference_Location :
Belfast
DOI :
10.1109/BIBM.2014.6999315
