[Current status and outlooks of acupuncture research driven by machine learning].

Journal: Zhongguo zhen jiu = Chinese acupuncture & moxibustion
PMID: 40229150

Abstract

The machine learning is used increasingly and widely in acupuncture prescription optimization, intelligent treatment and precision medicine, and has obtained a certain achievement. But, there are still some problems remained to be solved such as the poor interpretability of the model, the inconsistency of data quality of acupuncture research, and the clinical application of constructed models. Researches in future should focus on the acquisition of high-quality clinical and experimental data sets, take various machine learning algorithms as the basis, and construct professional models to solve various problems, so as to drive the high-quality development of acupuncture research.

Authors

  • Sixian Wu
    Department of Acupuncture and Moxibustion, First Teaching Hospital of Tianjin University of TCM, Tianjin 300193, China; National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin 300193; Graduate School, Tianjin University of TCM, Tianjin 301617.
  • Linna Wu
    First Clinical Medical School, Yunnan University of CM.
  • Yi Hu
    School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
  • Zhijie Xu
    Pacific Northwest National Laboratory, Richland, WA, United States.
  • Fan Xu
    Department of Public Health, Chengdu Medical College, Sichuan, China.
  • Hanbo Yu
    Department of Acupuncture and Moxibustion, First Teaching Hospital of Tianjin University of TCM, Tianjin 300193, China; National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin 300193; Graduate School, Tianjin University of TCM, Tianjin 301617.
  • Guiping Li
    Department of Management Science and Engineering, Business School, Ningbo University, No. 818, Fenghua Road, Ningbo 315211, China.

Keywords

External Resources

Popular Topics
Recent Journals