A Novel Knowledge Discovery Method for the Kidney Disease Diagnosis in TCM Based on Attribute Hierarchical Graphs

Author

Hong, Wenxue ; Zhao, Xiaolei ; Chen, Wendong ; Liu, Xulong ; Song, Jialin ; Jin, Hailong ; Yu, Jianping ; Ma, Yuan

Author_Institution

Biomed. Eng. Dept., Yanshan Univ., Qinhuangdao, China

fYear

2011

fDate

21-23 Oct. 2011

Firstpage

114

Lastpage

117

Abstract

On the basis of the theory of formal concept analysis (FCA), we proposed a new method based on hierarchical optimization formal context for generating attribute hierarchical graphs in this paper. By this method, we optimize the formal context of kidney disease, than build an attribute hierarchical graph, and discover the diagnosis knowledge in Traditional Chinese Medicine (TCM) at last. Finally, by combing former literature research we would like to show the availability and effectiveness of the proposed method.

Keywords

data mining; diseases; formal concept analysis; graph theory; kidney; medical computing; patient diagnosis; TCM; attribute hierarchical graphs; formal concept analysis; formal context; hierarchical optimization; kidney disease diagnosis; knowledge discovery; traditional chinese medicine; Blood; Context; Diseases; Fluids; Kidney; Medical diagnostic imaging; Optimization; Formal Concept Analysis; attribute hierarchical graphs; kidney disease; knowledge discovery;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation, Measurement, Computer, Communication and Control, 2011 First International Conference on

Conference_Location

Beijing

Print_ISBN

978-0-7695-4519-6

Type

conf

DOI

10.1109/IMCCC.2011.37

Filename

6153972