Methodology study of classification algorithm in TCM ZHENG diagnosis

Author

Na Chu ; Jie Li

Author_Institution

Dept. of Comput. Sci. & Technol., Dalian Neusoft Inst. of Inf., Dalian, China

fYear

2014

fDate

2-5 Nov. 2014

Firstpage

22

Lastpage

25

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedicine (BIBM), 2014 IEEE International Conference on

Conference_Location

Belfast

Type

conf

DOI

10.1109/BIBM.2014.6999315

Filename

6999315