产科人工智能:评估住院人员的能力和与ChatGPT的交互策略
David Desseauve1, Raphael Lescar2, Benoit de la Fourniere2
1Department of Women-Mother-Child, Gynaecology and Obstetrics Unit, Lausanne University Hospital, Lausanne, Switzerland; Department of Women-Mother-Child, Gynaecology and Obstetrics Unit, Grenoble Alpes, University Hospital, Grenoble, France.
使用人工智能 (AI) 进行学习的医疗人员表现出低AI能力,ChatGPT对有关妊娠并发症的临床查询提供了不准确的答案. 推结构化的AI识字计划,以安全地将AI整合到医学教育中.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 产科和妇科 产科和妇科
背景情况:
- 数字化转型正在增加医疗培训中的人工智能使用.
- 产科人员在评估期间与ChatGPT等人工智能工具的互动是不充分研究的.
- 居民自我报告的IT和AI能力需要评估.
研究的目的:
- 在临床评估期间评估产科医生与ChatGPT的相互作用.
- 评估居民自我报告的IT和AI能力.
- 探索AI响应的准确性及其与用户熟练程度的相关性.
主要方法:
- 一项半定性观察性研究,对14名产科住院生进行了研究.
- 居民查询的分类 (第三方,搜索引擎,以GPT为中心).
- 将ChatGPT的答案与专家验证的答案进行比较;描述和相关性分析.
主要成果:
- 居民表现出适度的IT,但AI能力较低.
- 怀孕期间急性肝硬化症的查询只给出了21%的准确答案,通常是由于缩写词的误解.
- 人工智能反应准确度与居民自我评估的人工智能/IT技能之间没有发现相关性;对人工智能培训的不满是常见的.
结论:
- 居民对人工智能的认知和实际掌握之间存在很大的差距.
- 临床上不准确但可信的AI反应突出了"随机"现象.
- 结构化的人工智能素养计划,包括快速工程,对于在医学教育和患者护理中安全有效地使用人工智能至关重要.
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