Support Vector Machine (SVM) and Traditional Chinese Medicine: Syndrome Factors Based an SVM from Coronary Heart Disease Treated by Prominent Traditional Chinese Medicine Doctors

Author

Wang, Jie ; He, Qingyong ; Yao, Kui-wu ; Rong, Wu ; Xing, Yanwei ; Yue, Zhang

Author_Institution

Cardiovascular Dept., China Acad. of Chinese Med. Sci., Beijing, China

Volume

2

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

176

Lastpage

180

Abstract

Support vector machines (SVM) have been widely used in many scientific research fields. This paper introduces an original study about the treating experiences of prominent traditional Chinese medicine (TCM) doctors on coronary heart disease (CHD) using SVM, and to investigate the general laws of prominent TCM doctors for treating CHD. A database of diagnosing and treating CHD was set up on the basis of 115 typical medical records. The syndrome factors and relevant studies were analyzed by SVM (data mining software Weka 3.4 is used). The quantitative diagnosis was confirmed and CHD characteristics were explained. The laws of medicate administration for 8 syndrome factors were summed up from prominent TCM doctors. Application of SVM will help to reveal innate regularity of experience of prominent TCM doctors, and deeply understand the academic thinking of them, in order to improve the level of treatment for CHD with TCM.

Keywords

cardiology; data mining; diseases; medical diagnostic computing; patient diagnosis; patient treatment; support vector machines; Weka 3.4; coronary heart disease diagnosis; data mining software; medicate administration; quantitative diagnosis; support vector machine; syndrome factors; traditional Chinese medicine; Cardiac disease; Cardiology; Data preprocessing; Databases; Helium; Machine learning; Medical diagnostic imaging; Medical treatment; Myocardium; Support vector machines; Support vector machines; traditional Chinese medicine;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2009. ICNC '09. Fifth International Conference on

Conference_Location

Tianjin

Print_ISBN

978-0-7695-3736-8

Type

conf

DOI

10.1109/ICNC.2009.735

Filename

5366522