JIANG Xiaochen,LIU Fudong,ZHANG Chuanlong,et al.The Current Issues and Thoughts on the Empowerment of Famous Doctors' Experience Inheritance by Artificial Intelligence[J].Journal of Traditional Chinese Medicine,2026,67(07):710-715.
JIANG Xiaochen,LIU Fudong,ZHANG Chuanlong,et al.The Current Issues and Thoughts on the Empowerment of Famous Doctors' Experience Inheritance by Artificial Intelligence[J].Journal of Traditional Chinese Medicine,2026,67(07):710-715.DOI: 10.13288/j.11-2166/r.2026.07.002.
The Current Issues and Thoughts on the Empowerment of Famous Doctors' Experience Inheritance by Artificial Intelligence
In the context of the modernization of traditional Chinese medicine (TCM), the inheritance of the experiences of famous doctors faces significant challenges due to its complex nonlinear characteristics and dynamic evolution. There are still issues in the current inheritance system, such as the homogenization of talent cultivation models, lack of standardized mentoring practices, and monotonous evaluation method, which hinder the systematic inheritance and innovative development of famous doctors' experiences. Based on a systematic review of the current state of artificial intelligence (AI)-assisted inheritance of famous doctors' experiences, this study explores innovative pathways for deep integration of modern information technologies with famous doctors' experiences from key dimensions, including data authenticity assurance, interdisciplinary collaboration mechanisms, and the establishment of dynamic inheritance standards. It proposes a paradigm shift in the inheritance of TCM famous doctors' experiences in the AI era, aiming to build a new TCM inheritance system of "digital intelligence empowerment and cross-disciplinary innovation", providing theoretical support and practical pathways for the inheritance of famous doctors' experiences in TCM.
UNG CY , LI H , CAO ZW , et al . Are herb-pairs of traditional Chinese medicine distinguishable from others? Pattern analysis and artificial intelligence classification study of traditionally defined herbal properties [J]. J Ethnopharmacol , 2007 , 111 ( 2 ): 371 - 377 .
ESTEVA A , ROBICQUET A , RAMSUNDAR B , et al . A guide to deep learning in healthcare [J]. Nat Med , 2019 , 25 ( 1 ): 24 - 29 .
HUANG Z , MIAO J , CHEN J , et al . A traditional Chinese medicine syndrome classification model based on cross-feature generation by convolution neural network: model development and validation [J]. JMIR Med Inform , 2022 , 10 ( 4 ): e29290 .
YAN J , CAI J , XU Z , et al . Tongue crack recognition using segmentation based deep learning [J]. Sci Rep , 2023 , 13 ( 1 ): 511 .
ZHOU J , LI S , WANG X , et al . Weakly supervised deep learning for tooth-marked tongue recognition [J]. Front Physiol , 2022 , 13 : 847267 . doi: 10.3389/fphys. 2022.847267 http://dx.doi.org/10.3389/fphys.2022.847267 .
HU J , YAN Z , JIANG J . Classification of fissured tongue images using deep neural networks [J]. Tech Health Care , 2022 , 30 ( S1 ): 271 - 283 .
YUAN L , YANG L , ZHANG S , et al . Development of a tongue image-based machine learning tool for the diagnosis of gastric cancer: a prospective multicentre clinical cohort study [J]. EClinicalMedicine , 2023 , 57 : 101834 . doi: 10.1016/j.eclinm.2023.101834 http://dx.doi.org/10.1016/j.eclinm.2023.101834 .
HUANG CH , WANG YM , SMITH S . Using high-dimensional features for high-accuracy pulse diagnosis [J]. Math Biosci Eng , 2020 , 17 ( 6 ): 6775 - 6790 .
DIMITRI GM . A short survey on deep learning for multimodal integration: applications, future perspectives and challenges [J]. Computers , 2022 , 11 ( 11 ): 163 .
PAN D , GUO Y , FAN Y , et al . Development and application of traditional Chinese medicine using AI machine learning and deep learning strategies [J]. Am J Chin Med , 2024 , 52 ( 3 ): 605 - 623 .
YANG K , DONG X , ZHANG S , et al . PresRecRF: herbal prescription recommendation via the representation fusion of large TCM semantics and molecular know-ledge [J]. Phytomedicine , 2024 , 135 : 156116 . doi: 10. 1016/j.phymed.2024.156116 http://dx.doi.org/10.1016/j.phymed.2024.156116 .
Construction and Clinical Validation of a Deep Learning-Based Automatic Measurement Model for Palmar Tilt and Radial Inclination in Distal Radius Fractures
An AI-Driven Research Pathway for Upholding Fundamental Principles and Breaking New Ground of Traditional Chinese Medicine Under the Guidance of Complexity Science
Construction and Application of a Real-World Cohort of Community-Acquired Pneumonia Based on a Multimodal Large-Scale Traditional Chinese Medicine Big Data Platform
Application of Artificial Intelligence and Large-Scale Model Algorithms in Research on Spleen-Stomach Diseases in Traditional Chinese Medicine
Strategies for Building an Artificial Intelligence-Empowered Trusted Federated Evidence-Based Analysis Platform for Spleen-Stomach Diseases in Traditional Chinese Medicine
Related Author
DAI Guoda
WANG Jianwei
WU Mao
KANG Bin
SHAO Yang
CUI Hengyan
LI Shaoshuo
ZHU Tingchen
Related Institution
Changzhou Hospital of Traditional Chinese Medicine
Suzhou Hospital of Traditional Chinese Medicine
Nanjing University of Posts and Telecommunications
Wuxi Hospital Affiliated to Nanjing University of Chinese Medicine
School of Intelligent Science and Technology,University of Science and Technology Beijing