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Research on model and algorithm of TCM constitution identification based on artificial intelligence

Author

Listed:
  • Bin Li

    (Shanghai Polytechnic University)

  • Qianghua Wei

    (Shanghai Jiaotong University)

  • Xinye Zhou

    (Shanghai Polytechnic University)

Abstract

In recent years, the research and application of artificial intelligence are developing rapidly. The application of artificial intelligence in medical image judgment has achieved good results in accuracy and speed. As big data and computing power increase, artificial intelligence will find more applications in medicine and health. In this paper, the artificial intelligence technology is applied to the judgment of Traditional Chinese Medicine (TCM) constitutional type. Using the model and algorithm of neural network, the fuzzy linguistic variables are expressed in value of membership degree to construct the nine standard TCM constitutional types as the basic sample data. Then it is combined with the judgment results of several TCM doctors to form new sample data and the model is trained by algorithm. The trained model is used to help TCM to classify individuals’ constitution. The simulation results show that the model achieves a good result by learning the sample data.

Suggested Citation

  • Bin Li & Qianghua Wei & Xinye Zhou, 2021. "Research on model and algorithm of TCM constitution identification based on artificial intelligence," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 988-1003, November.
    • Handle: RePEc:spr:jcomop:v:42:y:2021:i:4:d:10.1007_s10878-019-00486-y
    DOI: 10.1007/s10878-019-00486-y
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    References listed on IDEAS

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    1. Xiaohui Liu & Ni Zou & Dan Zhu & Dan Wang, 2019. "Influencing factors analysis and modeling of hospital-acquired infection in elderly patients," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 248-270, January.
    2. Feng Zhang & Jing Li & Junxiang Fan & Huili Shen & Jian Shen & Hua Yu, 2019. "Three-dimensional stable matching with hybrid preferences," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 330-336, January.
    3. Wei Gao & Wuping Bao & Xin Zhou, 2019. "Analysis of cough detection index based on decision tree and support vector machine," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 375-384, January.
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