基于数字病理与人工智能的病理学智慧教学体系构建与展望OA

Pathology serves as a critical bridge between basic and clinical medicine.Histopathological interpreta-tion is the cornerstone of disease diagnosis and represents one of the most fundamental yet challenging components of pathology education.Traditional teaching using glass slides is constrained by limited specimen preservation,insuffi-cient access to representative and rare cases,restrictions on time and location,and unequal teaching resources,mak-ing it difficult to meet the growing demands for standardized and individualized pathology training.The rapid develop-ment of digital pathology,artificial intelligence(AI),and large language model(LLM)has created new opportunities for transforming pathology education.This article systematically elaborates the construction and practical implementa-tion of a smart pathology education system(SPES),covering key modules including digital case repositories,AI-assisted standardized slide interpretation,LLM-enabled personalized learning,integrated problem-based learning(PBL)and case-based learning(CBL),virtual reality(VR)-based gross pathology simulation training,and multidi-mensional assessment throughout the educational continuum.Current challenges in AI-enabled pathology education are discussed,and potential strategies for future optimization are proposed.This review provides a practical framework for developing SPES and advancing the digital transformation of pathology training.