Multi-SVM based differential diagnostics in TCM

Author

Yan, Jian-jun ; Wang, Yi-Qin ; Xu, Zhao-Xia ; Liu, Guo-Ping ; Li Fu-Feng ; Guo, Rui ; Shen, Yong ; Xia, Chun-ming

Author_Institution

Center for Mechatron. Eng., East China Univ. of Sci. & Technol., Shanghai, China

Volume

1

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

111

Lastpage

114

Abstract

The differential diagnostics of traditional Chinese medicine is the kernel of TCM. The objective study of TCM diagnostics is a research hot spot at present. The differential diagnostics process of TCM is very complex and nonlinear. Support vector machine (SVM) is a novel method to establish the diagnosis model of TCM. In this paper, the differential diagnostics model is constructed base on multi-SVM. A comparison is made between Gaussian and poly kernel functions in SVM for differential diagnostics. The model based on multi-SVM presented can deal with accompanying syndromes better. The model can provide a new way to solve TCM differential diagnostics.

Keywords

Gaussian processes; learning (artificial intelligence); medical diagnostic computing; pattern classification; support vector machines; Gaussian kernel function; TCM; differential diagnostics process; multiSVM; pattern classification; poly kernel function; supervised learning; support vector machine; traditional Chinese medicine; Artificial neural networks; Biomedical imaging; Clinical diagnosis; Diseases; Kernel; Mechatronics; Medical diagnostic imaging; Neural networks; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

IT in Medicine & Education, 2009. ITIME '09. IEEE International Symposium on

Conference_Location

Jinan

Print_ISBN

978-1-4244-3928-7

Electronic_ISBN

978-1-4244-3930-0

Type

conf

DOI

10.1109/ITIME.2009.5236452

Filename

5236452