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A Deep Learning Approach for Tongue Diagnosis

  • Meng Xiao
  • Guozheng Liu
  • Yu Xia
  • Hao XuEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 921)

Abstract

With the improvement of living standards, people are paying more attention to healthcare, but there is still a long way to go to improve healthcare. A usable, intelligent aided diagnosis measure can be helpful for people to achieve daily health management. Several studies suggested that tongue features can directly reflect a person’s physical state. In this paper, we apply tongue diagnosis to daily health management. To this end, this paper proposes and implements a classification model of tongue image syndromes based on convolutional neural network and carries out an experiment to verify the feasibility and stability of the model. Finally, a tongue diagnosis platform that can be used for daily health management is implemented. In the two-class experiment, our model has achieved a good result. In addition, our model performs better on classifying the tongue image syndrome compared with traditional machine learning methods.

Keywords

Healthcare Health management Tongue image diagnosis Convolutional neural network 

Notes

Acknowledgements

This research was funded by the [Development Project of Jilin Province of China] grant number [20160414009GH, 20170101006JC, 20160204022GX], the [National Natural Science Foundation of China] grant number [61472159, 71620107001, 71232011], the [Jilin Provincial Key Laboratory of Big Date Intelligent Computing] grant number [20180622002JC]. The Premier-Discipline Enhancement Scheme was supported by Zhuhai Government and Premier Key-Discipline Enhancement Scheme was supported by Guangdong Government Funds.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.College of Computer Science and TechnologyJilin UniversityChangchunChina
  2. 2.School of ManagementJilin UniversityChangchunChina
  3. 3.Department of Computer Science and TechnologyZhuhai College of Jilin UniversityZhuhaiChina

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