人工智能时代的居民教育
1From the Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD.
Journal of computer assisted tomography
|December 4, 2024
概括
放射学教育工作者必须为居民制定人工智能 (AI) 课程. 这确保了未来的放射科医生能够有效地使用人工智能工具,并保持日常实践中必不可少的临床技能.
科学领域:
- 医学成像医学成像
- 放射学信息学 放射学信息学
- 医学中的人工智能
背景情况:
- 人工智能 (AI) 越来越与放射学相关.
- 人工智能在疾病检测和报告方面提供了潜在的好处.
- 人工智能可能会对放射科医生的角色和实践产生重大影响.
研究的目的:
- 概述放射学教育工作者在AI课程开发中的责任.
- 强调居民需要了解人工智能资源.
- 确保居民在AI知识的同时获得基本技能.
主要方法:
- 不适用 (概念论文/立场论文).
- 专注于教育战略和课程设计原则.
主要成果:
- 不适用 (概念论文/立场论文).
- 突出了结构化的AI教育的必要性,为放射科住院医生.
结论:
- 放射学实习课程必须整合人工智能教育.
- 国家协会的合作努力和支持对于课程开发至关重要.
- 准备居民成为人工智能管家对于放射学的未来至关重要.
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