Applications and Challenges of Artificial Intelligence-Empowered Core Competencies in Standardized Ophthalmology Residency Training

Corresponding author: liao xuan, aleexand@163.com

DOI: 10.12201/bmr.202609.00001

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  Abstract: Standardized residency training (SRT) is a core stage for medical students to transition into specialized ophthalmologists. Currently, ophthalmology residency training in China faces multiple dilemmas, including uneven distribution of regional resources, difficulty in internalizing the expanding knowledge system, insufficient clinical practice opportunities, and outdated traditional teaching models. The rapid development of artificial intelligence (AI) provides important opportunities for the digital-intelligent transformation of ophthalmology residency training.Grounded in the concept of competency-based medical education, this paper systematically sorts out the enabling application pathways of AI across the six core competency dimensions, and clarifies the boundaries of human-machine collaboration and corresponding prevention and control mechanisms for each dimension. It further analyzes the integration challenges and targeted countermeasures from five aspects: technical reliability, data ethics, cognitive development, implementation conditions, and institutional norms. This study aims to provide theoretical references and practical insights for cultivating new-era ophthalmologists equipped with both clinical competence and digital intelligence literacy.

  Key words: artificial intelligence; ophthalmology; residency training; core competencies; medical education

  Submit time: 1 September 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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