医学生人工智能素养能力清单与测评框架专家共识(2025年版)OA

To cultivate composite medical professionals capable of adapting to the development of intel-ligent healthcare,this consensus is grounded in the competency-based medical education,integrating the compe-tency model and Miller's pyramid of clinical competence.A two-round Delphi method involving a multidiscipli-nary expert panel was conducted,combined with a systematic literature review,to develop a 21-indicator artifi-cial intelligence(AI)literacy competency list for medical students across three domains:knowledge(8 indica-tors),skills(8 indicators),and attitudes(5 indicators).Furthermore,the consensus proposes a practical assessment system:standardized testing for the knowledge domain,situational judgment tests for the attitudes domain,and objective structured clinical examinations incorporating AI-related scenarios for the skills domain.In addition,a longitudinal assessment strategy spanning the phases of admission,preclinical training,and clini-cal training is recommended.The competency list and assessment framework established in this consensus demon-strate strong scientific rigor,authority,and practical applicability,and can serve as an important reference for medical schools seeking to advance the deep integration of AI and medical education and to cultivate composite medical talents suited to the era of intelligent healthcare.