数智技术在名老中医经验传承中的应用与思考OA

The inheritance of veteran traditional Chinese medicine(TCM)practitioners'expertise constitutes a core element in the development of TCM.While traditional inheritance modes have played a significant historical role,they demonstrate complementarity with digital intelligence-enabled approaches when addressing contemporary demands such as tacit knowledge transformation and large-scale inheritance.This paper reviews the key pathways and current research status of digital intelligence technologies in inheriting veteran TCM practitioners'experience.Specifically,text structuring techniques including word segmentation and named entity recognition are employed to extract and semantically normalize information from TCM literature.Data analysis techniques such as clustering analysis and graph neural networks are utilized to quantify prescription patterns and syndrome differentiation logic.Knowledge graphs are applied to systematically organize and visually represent veteran TCM practitioners'experience.Large language models are integrated to intelligently present digitized expertise.Building on these outcomes,inheritance platforms and auxiliary diagnosis systems are ultimately constructed to enable the digital applications of veteran TCM practitioners'experiences.However,this field still faces challenges including insufficient data standardization,difficulties in modeling the holistic and dynamic nature of TCM,ambiguous role posi-tioning,and unclear ethical responsibility frameworks.Looking forward,efforts should be focused on promoting the construction of cross-institutional trusted data spaces at the data level,deepening the human-machine integration mechanism at the mode level,and building open collaborative systems at the application level.The deepened application of digital intelligence technologies will shift the inheritance of veteran practitioners'expertise from a one-way,static knowledge preservation model toward a bidirectional,dynamic interactive learning and human-machine collaborative paradigm.