聊天GPT与医生衍生的药物相关问题的答案
Ole Kl Helgestad1, Astrid J Hjelholt1, Søren V Vestergaard2
1Department of Clinical Pharmacology, Aalborg University Hospital.
Danish medical journal
|February 12, 2025
概括
像ChatGPT这样的大型语言模型为制药问题提供高质量的答案. 虽然ChatGPT 4.0表现出强的性能,但它缺乏参考和临床解释,限制了其作为主要信息来源的使用.
科学领域:
- 人工智能在医学中的应用
- 自然语言处理自然语言处理.
- 临床决策支持 临床决策支持
背景情况:
- 医疗界对大型语言模型 (LLM) 的兴趣日益增长.
- 在制药咨询中对LLM的潜在应用正在调查中.
- 在医疗保健环境中LLMs的临床影响和实用性需要进一步评估.
研究的目的:
- 评估ChatGPT 3.5和4.0在药物咨询中的表现.
- 将AI生成的答案与人类医生提供的答案进行比较.
- 在现实环境中评估LLM响应的质量和临床相关性.
主要方法:
- 对49个药物咨询询问的回顾性分析.
- 将ChatGPT 3.5和4.0的答案与医生生成的答案进行比较.
- 评估答案质量和临床相关性.
主要成果:
- 在98%的案例中,ChatGPT 4.0提供了与医生同等或更好的答案.
- 在80%的案例中,ChatGPT 3.5 获得了类似的评分.
- 答案缺乏参考文献,并且并不总是优先考虑临床相关性.
结论:
- 聊天GPT 4.0显示了与毒品有关的查询的高质量响应.
- 由于没有参考文献和偶尔的有限临床解释,限制了其作为主要信息来源的使用.
- 虽然LLM表现有前途,但需要进一步开发以获得全面的临床应用.
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