评估生成人工智能作为放射学居民报告起草的教育工具
Antonio Verdone1, Aidan Cardall2, Fardeen Siddiqui2
1New York University Grossman School of Medicine, Department of Radiology.
Journal of the American College of Radiology : JACR
|December 26, 2025
概括
一个符合HIPAA标准的GPT-4o系统有效地为放射科医生住院乳腺成像报告提供自动反. 这种人工智能工具显示出与参与放射科医生的高度一致,并被评为有用,支持放射学教育.
科学领域:
- 医疗成像医学成像
- 医疗保健中的人工智能
- 放射学教育 放射学教育
背景情况:
- 放射科住院医生需要及时,个性化的反,以培养技能.
- 临床工作量限制了放射科医生提供全面指导的能力.
- 自动反系统可能可以实时弥合这一差距.
研究的目的:
- 评估符合HIPAA标准的GPT-4o系统,用于对居民乳腺成像报告的自动反.
- 评估人工智能生成的反的准确性和有用性,与参加放射科医生相比.
- 确定AI作为放射学教育中的可扩展工具的潜力.
主要方法:
- 分析了5000名住院护理人员的乳房成像报告对.
- GPT-4o被要求识别居民报告中的常见错误.
- 一项读者研究,包括4名主治放射科医生和4名住院医生,评估了GPT-4o对100对报告对的反.
主要成果:
- GPT-4o表现出强烈的同意与错误识别 (90.5%,78.3%,90.4%) 的参与共识.
- 在大多数情况下,AI反被认为是有帮助的 (89.8%,83.0%,92.0%).
- 用GPT-4o取代人类读者并没有显著改变读者之间的协议.
结论:
- GPT-4o可靠地识别了放射科住院医生报告中的关键教育错误.
- 人工智能系统显示出作为一个可扩展的工具来增强放射学教育的潜力.
- 自动反可以补充放射学培训中的传统指导.
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