人工智能的临床知识和推理能力 麻醉学中的大型语言模型:对ABA考试的比较研究
medRxiv : the preprint server for health sciences
|June 9, 2023
概括
GPT-4成功通过了美国麻醉学会的考试,证明了先进的临床推理. 其他人工智能模型,如GPT-3和Bard没有通过,强调了GPT-4在麻醉实践中的卓越医学知识.
科学领域:
- 医学的人工智能 (AI)
- 临床推理评估评估
- 大型语言模型 (LLM)
背景情况:
- 人工智能在医学领域越来越受欢迎,最近的LLM显示了先进的语言技能.
- 以前的研究集中在一般医学知识上,但临床和专业推理仍未得到充分探索.
- 美国麻醉学会 (ABA) 考试是麻醉知识和能力的综合测试.
研究的目的:
- 在专业医疗环境中评估LLM (GPT-3,Bard,GPT-4) 的临床知识和推理能力.
- 为了比较他们在美国麻醉学会 (ABA) 考试中的表现,这是麻醉知识和能力的综合测试.
- 与专家人类检查员一起评估AI的反应.
主要方法:
- LLM (GPT-3,Bard,GPT-4) 在ABA考试的书面部分进行了测试.
- 两位经过董事会认证的麻醉师评估了人工智能为口试部分生成的答案.
- 人工智能模型的性能基于准确性和专家评估进行了比较.
主要成果:
- GPT-4成功通过了书面的ABA考试,在基本部分获得78%,在高级部分获得80%.
- GPT-3和Bard的得分明显较低:GPT-3 (58%基本,50%高级) 和Bard (47%基本,46%高级).
- 专家考官认为GPT-4很可能通过口头ABA考试;只有GPT-4才能进入这个阶段.
结论:
- 与GPT-3和Bard相比,GPT-4在麻醉学中展示了卓越的临床知识和推理.
- 人工智能模型的性能因主题而异,这表明培训数据质量存在差异.
- 这项研究预测了AI在特定麻醉学子专业领域的早期整合.
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