Title: Study on intelligent syndrome differentiation in Traditional Chinese Medicine based on multiple information fusion methods

Authors: Yi-qin Wang, Hai-xia Yan, Rui Guo, Fu-feng Li, Chun-ming Xia, Jian-jun Yan, Zhao-xia Xu, Guo-ping Liu, Jin Xu

Addresses: School of Basic Medicine, Shanghai University of Traditional Chinese, Shanghai 201203, China. ' School of Basic Medicine, Shanghai University of Traditional Chinese, Shanghai 201203, China. ' Centre for Information and Science and Technology of TCM, Shanghai University of Traditional Chinese, Shanghai 201203, China. ' Centre for Teaching Experience, Shanghai University of Traditional Chinese, Shanghai 201203, China. ' Centre for Mechatronics Engineering, East China University of Science and Technology, Shanghai 200237, China. ' Centre for Mechatronics Engineering, East China University of Science and Technology, Shanghai 200237, China. ' School of Basic Medicine, Shanghai University of Traditional Chinese, Shanghai 201203, China. ' School of Basic Medicine, Shanghai University of Traditional Chinese, Shanghai 201203, China. ' School of Basic Medicine, Shanghai University of Traditional Chinese, Shanghai 201203, China

Abstract: Numerous researchers have taken the solid step forward towards the objectification research of Traditional Chinese Medicine (TCM) four diagnostic methods. However, it is deficient in studies on information fusion of the four diagnostic methods. We establish four-diagnosis syndrome differentiation model of TCM based on information fusion technology. The objective detection instruments of four-diagnostic method are applied to collect four-diagnosis objective information of 506 cases of clinical heart-system patients. Then multiple information fusion methods are adopted to establish recognition model of syndromes. The results of our experiments show that recognition rates of the six syndromes using multi-label learning is better than OCON artificial neural network and multiple support vector machine.

Keywords: four diagnosis; syndrome differentiation; information fusion; artificial intelligence; traditional Chinese medicine; syndrome recognition; multi-label learning; artificial neural networks; ANNs; support vector machines; SVM; heart disease.

DOI: 10.1504/IJDMB.2011.041554

International Journal of Data Mining and Bioinformatics, 2011 Vol.5 No.4, pp.369 - 382

Published online: 26 Jul 2011 *

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