聊天GPT:一个有用的工具为医学学生在放射学教育?
Musab Sirag1, Brian M Moloney2,3
1Portiuncula University Hospital, Ballinasloe, Galway, Ireland.
像ChatGPT这样的大型语言模型在推适当的成像调查方面显示出100%的准确性,超过医学学生和初级医生. 这表明LLM可以成为放射学教育和临床决策支持的宝贵工具.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 放射学 放射学是一门学科.
背景情况:
- 大型语言模型 (LLM) 正在被探索为医学培训中的教育工具,特别是在放射学中.
- 这项研究评估了ChatGPT在推各种临床情景的成像研究中的准确性.
研究的目的:
- 评估ChatGPT在推适当的成像调查方面的准确性.
- 将ChatGPT的表现与医学学生和初级医生的表现进行比较.
- 探索LLMs作为放射学教育工具的潜力.
主要方法:
- 聊天GPT-4 (2024年3月) 接受了基于美国放射学学院适当性标准 (ACR-AC) 的12个病例问卷.
- 将ChatGPT的建议与ACR-AC的指导方针进行了比较,并对160名最后一年的医学学生和初级医生的表现进行了比较.
主要成果:
- 聊天GPT与专家小组建议达到了100%的一致性 (12/12个案例).
- 学生/博士队列的一致率达到了68.0%.
- 绩效的差异是统计学上显著的 (p < 0.05).
结论:
- 根据指南,ChatGPT在推适当的成像调查方面表现出高准确度.
- 在放射学教育中,LLM显示出作为有价值的附加剂的潜力,帮助经验较少的临床医生.
- 在现实世界的临床环境中需要进一步验证.
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