Reflections on the Application of Large Models Empowering the Inheritance and Innovative Development of Traditional Chinese Medicine

Corresponding author: xiaoyong, xy_1015@126.com

DOI: 10.12201/bmr.202608.00012

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  Abstract: Purpose and Significance? Artificial intelligence represented by large models has become a core pillar for advancing the digital and intelligent transformation of traditional Chinese medicine (TCM). This paper explores the current development and application status of TCM large models, provides references for standardizing their research and development as well as large-scale implementation, and facilitates the high-quality digital and intelligent development of TCM.Methods and Procedures? A total of 53 artificial intelligence large models in the TCM field were selected as research samples. The development trend of the TCM large model industry was systematically sorted out and analyzed from multiple dimensions including R D entities, technical architecture, dataset construction, application scenarios and application effects. Results and Conclusion? The development of TCM large models is faced with bottlenecks such as imperfect standards, specifications and evaluation systems, insufficient supply of high-quality professional data, lack of a commercial closed-loop mechanism, inadequate adaptability between technology and scenarios, and shortage of interdisciplinary professionals. Combined with the high-quality development demands of the TCM industry, targeted countermeasures and suggestions are proposed from the aspects of top-level design, construction of industrial standards and professional evaluation systems, supply of high-quality TCM data elements, multimodal technology integration and scenario adaptation, and cultivation of interdisciplinary talents integrating TCM and artificial intelligence, so as to provide a reference for the healthy and sustainable development of TCM large models.

  Key words: TCM; Large Model; Artificial Intelligence; Inheritance and Innovation

  Submit time: 5 August 2026

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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