Abstract: Currently,the classification standards and evaluation methods for various types of talent in the field of Traditional Chinese Medicine (TCM) in China remain insufficient,with numerous challenges persisting in the implementation of classified evaluations for scientific and technological personnel.This study aims to explore a comprehensive classified evaluation system for scientific and technological talents in the TCM field and to provide recommendations for advancing talent evaluation reform.Adhering to the principles of scientific validity,feasibility,and relevance,the study preliminarily selected 26 evaluation indicators from both theoretical and practical perspectives.Two evaluation indicator systems—for basic research-oriented and applied research-oriented talent—were constructed by using the grey dynamic clustering-rough set reduction method.The entropy-weighted TOPSIS method was then applied to empirically test the robustness of these systems.Overall,the constructed evaluation models effectively enable differentiated assessment of basic and applied research personnel.To further deepen evaluation reform in the TCM field,the study recommends enhancing the talent database for scientific and technological personnel to ensure comprehensive data support,promoting a people-centered evaluation philosophy,establishing diversified evaluation mechanisms,and continuously developing evaluation indicators with distinctive TCM characteristics.