Title :
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
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;
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
DOI :
10.1109/ITIME.2009.5236452
