文献类型：会议论文

英文题名：Study on intelligent syndrome differentiation in Traditional Chinese Medicine based on multiple information fusion methods

作者：Wang, Yi-qin[1];Yan, Hai-xia[1];Guo, Rui[2];Li, Fu-feng[3];Xia, Chun-ming[4];Yan, Jian-jun[4];Xu, Zhao-xia[1];Liu, Guo-ping[1];Xu, Jin[1]

机构：[1]Shanghai Univ Tradit Chinese, Sch Basic Med, Shanghai 201203, Peoples R China;[2]Shanghai Univ Tradit Chinese, Ctr Informat & Sci & Technol TCM, Shanghai 201203, Peoples R China;[3]Shanghai Univ Tradit Chinese, Ctr Teaching Experience, Shanghai 201203, Peoples R China;[4]E China Univ Sci & Technol, Ctr Mechatron Engn, Shanghai 200237, Peoples R China

会议论文集：International Workshop on Information Technology for Chinese Medicine (ITCM)/IEEE International Conference on Bioinformatics and Bio-Medical Engineering (IEEE-BIBM)

会议日期：DEC 18, 2010

会议地点：Hong Kong, PEOPLES R CHINA

语种：英文

外文关键词：four-diagnosis; syndrome differentiation; information fusion; artificial intelligence; traditional Chinese medicine

摘要：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.