大型语言模型在医学和外科手术中的临床应用:范围审查
Eric Nan Liang1, Sophia Pei1, Phillip Staibano2,3
1Michael G. DeGroote School of Medicine, McMaster University, Canada.
The Journal of international medical research
|July 4, 2025
概括
大型语言模型 (LLM) 越来越多地用于医学,主要用于数据提取. 大多数LLM在临床采用之前需要进一步验证,强调需要标准化的评估.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 大型语言模型的临床应用.
背景情况:
- 大型语言模型 (LLM) 在临床医学和外科手术中的整合正在迅速发展.
- 了解当前的LLM特征,应用和准备就绪对于安全实施至关重要.
研究的目的:
- 在临床医学和外科手术中对LLM利用进行全面的范围审查.
- 分析模型特征,临床应用,并评估其在医疗保健环境中采用的准备.
主要方法:
- 根据PRISMA-scoping和JBI的方法进行范围审查.
- 在EMBASE,PubMed,CINAHL和IEEE Xplore搜索了2018年至2023年间发表的文章.
- 从156项纳入研究中提取了研究类型,临床专业,模型架构,培训,应用和性能指标的数据.
主要成果:
- 主要用于数据提取 (69.9%),临床建议 (11.5%) 和报告生成 (9.0%).
- 聊天GPT-3.5,聊天GPT-4和BERT是常见的模型;专有模型比开源更频繁地使用.
- 只有25.0%的研究认为模型已经准备好临床使用,大多数需要进一步验证;F-score和AUC是主要指标.
结论:
- 在临床医学中,LLM的应用越来越多,从数据提取转向决策等更高级别的任务.
- 在LLM架构,评估和报告中存在显著的异质性,需要标准化.
- 开发透明的评估框架对于安全可靠地融入临床工作流程至关重要.
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