您当前的位置:
首页 >
文章列表页 >
Construction and validation of a neural network-based traditional Chinese medicine expert diagnostic model for cervical spondylosis
Information and Statistics | 更新时间:2026-02-03
    • Construction and validation of a neural network-based traditional Chinese medicine expert diagnostic model for cervical spondylosis

    • Experts from Wangjing Hospital of the Chinese Academy of Traditional Chinese Medicine have constructed and validated a cervical spondylosis diagnosis and treatment model based on a multi-layer perceptron neural network. They have also developed an open and shared interactive artificial intelligence assisted decision-making platform, providing a new tool for improving the standardization and efficiency of cervical spondylosis diagnosis and treatment.
    • Journal of Beijing University of Traditional Chinese Medicine   Vol. 49, Issue 1, Pages: 139-148(2026)
    • DOI:10.3969/j.issn.1006-2157.2026.01.017    

      CLC: R241.4;TP183
    • Received:02 July 2025

      Published:30 January 2026

    移动端阅览

  • YANG Guangyi, FENG Minshan, HAN Changxiao, et al. Construction and validation of a neural network-based traditional Chinese medicine expert diagnostic model for cervical spondylosis[J]. Journal of Beijing University of Traditional Chinese Medicine, 2026, 49(1): 139-148. DOI: 10.3969/j.issn.1006-2157.2026.01.017.

  •  
  •  

0

Views

0

下载量

0

CSCD

Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

Performance evaluation of machine learning algorithms on the pattern elements of "qi deficiency" assisted diagnosis
Construction and development of a discipline system for the science of Chinese Materia Medica from the perspective of systems science
Multicenter retrospective analysis of 1 055 severe cases of COVID-19 treated by integrated Chinese and Western medicine or Western medicine based on LightGBM and SHAP
Discussion on the process of theorization of TCM based on “data feeding” model
Screening anti-fibrosis Chinese medicinal compounds based on machine learning

Related Author

Chenjie Shu
Hao Liang
Shuming Liu
Yun Wang
QIAO Yanjiang
ZHANG Jiwang
Hai Jin
Wei Li

Related Institution

School of Chinese Materia Medica, Beijing University of Chinese Medicine
Beijing University ofChinese Medicine
Chengdu University of Traditional Chinese Medicine
National Engineering Research Center for Big Data Technology and Systems, Key Laboratory of Service Computing Technology and Systems of Ministry of Education, Key Laboratory of Computing Cluster and Grid Computing of Hubei Province, School of Computer Science and Technology of Huazhong University of Science and Technology
Department of Emergency, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
0