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人工智能和疼痛医学教育:医疗学员的好处和陷
Michael Glicksman1, Sheri Wang2, Samir Yellapragada3
1Department of Physical Medicine and Rehabilitation, University of Pittsburgh Medical Center (UPMC), Pittsburgh, Pennsylvania, USA.
Pain practice : the official journal of World Institute of Pain
|November 26, 2024
概括
人工智能 (AI) 为疼痛医学实习生教育提供了好处,但目前的局限性需要谨慎使用. 大型语言模型 (LLM) 是有前途的,但需要进一步研究才能独立应用.
科学领域:
- 医疗教育 技术 技术 医学教育
- 人工智能在医学中的应用
- 疼痛管理培训 疼痛管理培训
背景情况:
- 人工智能 (AI) 越来越多地融入医疗实践,包括疼痛医学.
- 大型语言模型 (LLM) 是人工智能的一个突出的子集,应用越来越多.
- 有限的研究存在于AI对疼痛医学实习生教育的具体影响.
研究的目的:
- 评估人工智能在疼痛医学实习生教育中的潜在好处和缺点.
- 通过试点研究评估LLMs在增强或阻碍疼痛医学教育中的作用.
主要方法:
- 进行了关于人工智能在疼痛医学方面的文献审查,以确定益处和陷.
- 实施了一项试点质量改进项目,使用三个领先的LLM:ChatGPT Plus,Google Bard和Bing AI.
- 通过提出与疼痛医学教育相关的多选择题来评估LLM绩效.
主要成果:
- 潜在的好处包括改进成像解释,技能培训,个性化学习和知识总结.
- 确定的陷包括成本差异,偏见,抄袭问题以及缺乏专门的疼痛医学培训.
- 聊天GPT Plus表现出最高的准确性 (16/17),而LLM则在基本的第一阶段问题上扎,在复杂的答案中表现出推理不一致.
结论:
- 人工智能作为疼痛医学学员的补充工具具有显著的潜力.
- 目前的局限性限制了AI在这个教育环境中的独立使用.
- 进一步的研究对于解决现有挑战和优化AI在疼痛医学培训中的整合至关重要.
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