Basic Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Center for Mechatronics Engineering, East China University of Science and Technology, Shanghai 200237, China.
Comput Math Methods Med. 2014;2014:938350. doi: 10.1155/2014/938350. Epub 2014 Mar 5.
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.
在中医(TCM)中,用于解决证候诊断问题的大多数算法都是浅层结构算法,而没有从大脑认知的角度考虑。然而,在临床实践中,症状(征象)与证候之间存在复杂的非线性关系。因此,我们采用深度学习和多标签学习来构建中医慢性胃炎症候诊断模型。结果表明,深度学习可以提高证候识别的准确性。此外,该研究将为构建证候诊断模型提供参考,并指导临床实践。