卓越
劳动力发展
终身学习
专业发展
课程
工程伦理学
最佳实践
劳动力
质量(理念)
计算机科学
知识管理
叙述的
转化式学习
教育学
学习周期
质量管理
教师发展
学徒制
课程开发
教育技术
异步通信
学习风格
主动学习(机器学习)
异步学习
隐性知识
心理学
医学教育
新兴技术
持续专业发展
问责
政治学
作者
Andrew K. Moriarity,Shlomit A. Goldberg-Stein,Tessa Sundaram Cook,Catherine S. Giess,Richard E. Sharpe,Atul Bhanudas Shinagare,Ramin Khorasani
摘要
Radiology learning and development—encompassing both trainee education and lifelong professional learning—are undergoing rapid transformation driven by sustained growth in imaging volumes, persistent workforce constraints, increasing subspecialization, and evolving hybrid practice models that are reshaping radiologists’ work. The resulting pressures increasingly and directly compete with protected time for case-based teaching, mentorship, feedback, and deliberate practice, placing at risk the entire professional development cycle from training through practice. Meanwhile, virtual and asynchronous educational platforms are expanding access to teaching conferences, case libraries, mobile resources, microlearning opportunities, and global collaboration and introducing challenges related to engagement, curation, feedback, and procedural skill expertise. Peer-learning programs are also gaining momentum as an alternative to traditional score-based peer review, offering a structured nonpunitive approach to shared learning and practice improvement embedded within routine clinical work. In parallel, generative artificial intelligence and large language models are creating new opportunities for knowledge synthesis and educational support amidst important concerns regarding accuracy, bias, outdated information, and overreliance. In this AJR Expert Panel Narrative Review, we examine how these converging trends are reshaping radiology learning and development and provide consensus guidance for strengthening educational quality while sustaining diagnostic excellence and professional growth in contemporary practice.
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