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对临床决策支持任务的ChatGPT,谷歌搜索和Llama 2进行系统分析

Sarah Sandmann¹, Sarah Riepenhausen¹, Lucas Plagwitz¹

¹Institute of Medical Informatics, University of Münster, Münster, Germany.

Nature communications

|March 6, 2024

概括

大型语言模型 (LLM) 显示了医疗咨询的潜力. 在诊断和检查方面,GPT-4的表现优于GPT-3.5和谷歌,尽管治疗的准确性各不相同.

科学领域:

医疗信息学医疗信息学
医疗保健中的人工智能
临床决策支持临床决策支持

背景情况:

大众越来越多地使用大型语言模型 (LLM) 来寻找健康信息.
需要评估LLM在医疗应用中的临床准确性.

研究的目的:

评估GPT-3.5和GPT-4用于诊断,检查和治疗建议的临床准确性.
将LLM的表现与谷歌搜索和开源Llama 2模型进行比较.
确定医学问答中的LLMs的优点和弱点.

主要方法:

评估了110个不同的医疗病例.
GPT-4,GPT-3.5和两个Llama 2配置的比较.
与对诊断准确性的天真谷歌搜索进行基准测试.

主要成果:

与GPT-3.5和谷歌搜索相比,GPT-4在诊断和检查方面表现优越.
所有评估的模型在常见疾病方面表现比罕见疾病更好,除了治疗.
在该子研究中,Llama 2模型的性能略低.

结论:

像GPT-4这样的商业LLM显示出医学问题答案的巨大潜力.
弱点突出了需要监管和强大的AI在医疗保健.
开源的LLM为数据隐私和培训透明度提供了潜在的好处.

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