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

被引:11
|
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
关键词
four-diagnosis; syndrome differentiation; information fusion; artificial intelligence; traditional Chinese medicine;
D O I
10.1504/IJDMB.2011.041554
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
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.
引用
收藏
页码:369 / 382
页数:14
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