Deep Learning Based Syndrome Diagnosis of Chronic Gastritis
Joint Authors
Wang, Yi-Qin
Zheng, Wu
Lu, Xiong
Yan, Jian-Jun
Liu, Guo-Ping
Zhong, Tao
Qian, Peng
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-05
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Liu, Guo-Ping& Yan, Jian-Jun& Wang, Yi-Qin& Zheng, Wu& Zhong, Tao& Lu, Xiong…[et al.]. 2014. Deep Learning Based Syndrome Diagnosis of Chronic Gastritis. Computational and Mathematical Methods in Medicine،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-509749
Modern Language Association (MLA)
Liu, Guo-Ping…[et al.]. Deep Learning Based Syndrome Diagnosis of Chronic Gastritis. Computational and Mathematical Methods in Medicine No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-509749
American Medical Association (AMA)
Liu, Guo-Ping& Yan, Jian-Jun& Wang, Yi-Qin& Zheng, Wu& Zhong, Tao& Lu, Xiong…[et al.]. Deep Learning Based Syndrome Diagnosis of Chronic Gastritis. Computational and Mathematical Methods in Medicine. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-509749
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-509749