人工智能及其对放射学实习教育的影响:当前的挑战,机遇和未来的方向
Joshua Volin1, Marly van Assen2, Wasif Bala3
1Resident, Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia; Chief Resident of Diagnostic Radiology, Emory University.
Journal of the American College of Radiology : JACR
|July 14, 2025
概括
人工智能 (AI) 正在改变放射学,需要为住院人员提供结构化培训. 将人工智能教育,工具和伦理考虑纳入放射学课程中,对于未来的临床能力至关重要.
科学领域:
- 放射学 放射学是一门学科.
- 医学教育 医学教育
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 越来越多地融入放射学,影响工作流程和临床决策.
- 由于现有的需求,目前的放射学住院课程面临着适应全面的人工智能教育的挑战.
研究的目的:
- 讨论有效的居民人工智能培训的基本组成部分:教育,人工智能教育工具和临床实施.
- 探索克服课程限制的策略,并在临床实践中为AI准备居民.
主要方法:
- 审查目前的挑战在人工智能教育的放射学居民.
- 讨论潜在的解决方案,包括不同的教育轨道和外部课程.
- 分析人工智能驱动的教育工具的作用及其对学习的影响.
- 考虑道德方面的影响和结构化指导的必要性.
主要成果:
- 过度拥挤的课程对全面的AI教育构成了重大障碍.
- 纵向的教育轨道和外部课程可以增强AI知识的获取.
- 由人工智能驱动的教育工具为积极学习和改进理解提供了新的方法.
- 美国食品和药物管理局 (FDA) 批准的人工智能工具的扩散需要居民为临床整合做好准备.
结论:
- 居住计划必须调整课程以包括基于证据的AI教育.
- 对人工智能基础,工具和伦理的结构化指导对于未来的放射科医生来说至关重要.
- 培训应该使居民能够批判性地评估和利用AI,确保它增强,而不是取代临床专业知识.
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