代码有一天会运行代码吗? 语言模型在ACEM初级考试中的表现及其影响
Jesse Smith1, Philip Mc Choi2,3, Paul Buntine1,2
1Eastern Health Emergency Medicine Program, Eastern Health, Melbourne, Victoria, Australia.
大型语言模型 (LLM) 通过了澳大利亚紧急医疗学院的初级考试,显示了医学教育的前景. 在此紧急医疗评估中,GPT 4.0显著超过了候选人的平均表现.
科学领域:
- 人工智能在医学中的应用
- 医疗教育 技术 技术 医学教育
- 紧急医疗评估评估
背景情况:
- 大型语言模型 (LLM) 在专业医疗检查中表现有变化.
- 在紧急医疗评估中LLM的有效性尚未得到充分证实.
研究的目的:
- 评估著名的LLM在澳大利亚紧急医疗学院 (ACEM) 初级考试中的表现.
- 确定LLMs在紧急医疗培训和评估中的潜在实用性.
主要方法:
- 测试了三个领先的LLM (OpenAI的GPT系列,谷歌的Bard,微软的Bing聊天).
- 使用实践ACEM初级检查来评估表现.
主要成果:
- 所有评估的法学士都成功通过了ACEM初级考试.
- 与平均人类候选人相比,GPT 4.0表现出优越的表现.
结论:
- 法律学士学位显示出作为医疗教育和紧急医疗实践的有价值工具的潜力.
- 尽管通过了考试,但LLM的现有局限性需要进一步调查和讨论.
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