利用大型语言模型来增强麻醉学中的情绪智能培训
Monika Nanda1, Rodney A Gabriel2, Tetsuro Sakai1
1Department of Anesthesiology, University of North Carolina, Chapel Hill, North Carolina.
Anesthesiology
|July 8, 2025
概括
麻醉科医生需要情绪智能 (EI) 关键的病人护理. 大型语言模型 (LLM) 提供创新的培训工具,通过模拟场景来提高EI技能,改善沟通.
科学领域:
- 麻醉学 麻醉学
- 医学教育 医学教育
- 人工智能的人工智能
背景情况:
- 情绪智能 (EI) 对麻醉师在高风险的外科手术前沟通中至关重要.
- 疲劳和繁重的工作负载等压力因素可以在关键患者护理期间损害EI.
- 结构化的培训是必要的,以加强临床实践中的EI.
研究的目的:
- 探索大语言模型 (LLM) 的潜力,作为增强麻醉学情感智能培训的新工具.
- 研究如何利用LLM来创建定制的模拟场景,以提高临床医生的沟通技巧.
主要方法:
- 使用LLM生成各种各样的按需模拟场景.
- 场景的设计是为了通过专家对教学使用进行微调和验证.
- 课程简介 (LLMs) 促进了针对情感充满对话的量身定制培训模块的创建.
主要成果:
- LLM 证明了能够产生适合培训的同情反应的能力.
- 该技术允许为各种教学方法创建可定制的模拟场景.
- LLM可以提供可访问的补充工具,以加强临床医生的EI技能.
结论:
- 大型语言模型为补充麻醉学情感智能培训提供了一种创新且易于使用的方法.
- 通过LLM生成的模拟可以有效地为临床医生准备具有挑战性的人际交互.
- 虽然不取代人为主导的培训,但LLMs提供了一个有价值的补充,以加强在经验丰富的专家监督下,在术前环境中加强沟通和EI.
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