文献类型：期刊文献

英文题名：Deep Learning Based Syndrome Diagnosis of Chronic Gastritis

作者：Liu, Guo-Ping[1];Yan, Jian-Jun[2];Wang, Yi-Qin[1];Zheng, Wu[1];Zhong, Tao[2];Lu, Xiong[3];Qian, Peng[1]

机构：[1]Shanghai Univ Tradit Chinese Med, Basic Med Coll, Shanghai 201203, Peoples R China;[2]E China Univ Sci & Technol, Ctr Mechatron Engn, Shanghai 200237, Peoples R China;[3]Shanghai Univ Tradit Chinese Med, Technol & Expt Ctr, Shanghai 201203, Peoples R China

年份：2014

卷号：2014

外文期刊名：COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE

收录：;EI(收录号：20214511125301);WOS:【SCI-EXPANDED(收录号:WOS:000332890400001)】；

基金：This work was supported by the National Natural Science Foundation of China (Grant nos. 81270050, 30901897, and 81173199).

语种：英文

外文关键词：Diagnosis

摘要：In Traditional Chinese Medicine (TCM), most of the algorithms used to solve problems of syndrome diagnosis are superficial structure algorithms and not considering the cognitive perspective from the brain. However, in clinical practice, there is complex and nonlinear relationship between symptoms (signs) and syndrome. So we employed deep leaning and multilabel learning to construct the syndrome diagnostic model for chronic gastritis (CG) in TCM. The results showed that deep learning could improve the accuracy of syndrome recognition. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice.