Diagnostic Method of Diabetes Based on Support Vector Machine and Tongue Images
Joint Authors
Xu, Jia-Tuo
Tu, Li Ping
Hu, Xiao-juan
Cui, Ji
Zhang, Jianfeng
Chen, Qingguang
Huang, Jingbin
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-01-04
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Objective.
The purpose of this research is to develop a diagnostic method of diabetes based on standardized tongue image using support vector machine (SVM).
Methods.
Tongue images of 296 diabetic subjects and 531 nondiabetic subjects were collected by the TDA-1 digital tongue instrument.
Tongue body and tongue coating were separated by the division-merging method and chrominance-threshold method.
With extracted color and texture features of the tongue image as input variables, the diagnostic model of diabetes with SVM was trained.
After optimizing the combination of SVM kernel parameters and input variables, the influences of the combinations on the model were analyzed.
Results.
After normalizing parameters of tongue images, the accuracy rate of diabetes predication was increased from 77.83% to 78.77%.
The accuracy rate and area under curve (AUC) were not reduced after reducing the dimensions of tongue features with principal component analysis (PCA), while substantially saving the training time.
During the training for selecting SVM parameters by genetic algorithm (GA), the accuracy rate of cross-validation was grown from 72% or so to 83.06%.
Finally, we compare with several state-of-the-art algorithms, and experimental results show that our algorithm has the best predictive accuracy.
Conclusions.
The diagnostic method of diabetes on the basis of tongue images in Traditional Chinese Medicine (TCM) is of great value, indicating the feasibility of digitalized tongue diagnosis.
American Psychological Association (APA)
Zhang, Jianfeng& Xu, Jia-Tuo& Hu, Xiao-juan& Chen, Qingguang& Tu, Li Ping& Huang, Jingbin…[et al.]. 2017. Diagnostic Method of Diabetes Based on Support Vector Machine and Tongue Images. BioMed Research International،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1138824
Modern Language Association (MLA)
Zhang, Jianfeng…[et al.]. Diagnostic Method of Diabetes Based on Support Vector Machine and Tongue Images. BioMed Research International No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1138824
American Medical Association (AMA)
Zhang, Jianfeng& Xu, Jia-Tuo& Hu, Xiao-juan& Chen, Qingguang& Tu, Li Ping& Huang, Jingbin…[et al.]. Diagnostic Method of Diabetes Based on Support Vector Machine and Tongue Images. BioMed Research International. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1138824
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1138824