| Literature DB >> 21954670 |
Yi-Qin Wang1, Hai-Xia Yan, Rui Guo, Fu-Feng Li, Chun-Ming Xia, Jian-Jun Yan, Zhao-Xia Xu, Guo-Ping Liu, Jin Xu.
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.Entities:
Mesh:
Year: 2011 PMID: 21954670 DOI: 10.1504/ijdmb.2011.041554
Source DB: PubMed Journal: Int J Data Min Bioinform ISSN: 1748-5673 Impact factor: 0.667