医学中关于大语言模型的100个最常被引用的文章:参考文献分析
Zhi-Qiang Li1, Runbing Xu2, Xin-Ran Gong3
1Centre for Evidence-based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Digital health
|September 15, 2025
概括
大型语言模型 (LLM) 正在改变医学研究,最受引用的文章集中在临床决策支持和药物发现中的AI应用上. 本文献分析突出了医学LLM的关键趋势和未来方向.
科学领域:
- 图书统计学 图书统计学
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 大型语言模型 (LLM) 在医学研究中越来越有影响力.
- 要了解引用趋势和LLM在医学上的影响,需要进行文献计量分析.
- 本研究确定和描述了医学领域关于LLM的最常被引用的文章.
研究的目的:
- 为了对医学LLM中最常被引用的100篇文章进行文献分析.
- 评估高影响力LLM研究在医疗保健中的影响和特征.
- 确定新兴的研究主题,并指导LLMs在医学中的未来应用.
主要方法:
- 在科学网络数据库 (2022-2025) 中索引的文章的图书统计分析.
- 搜索术语包括"LLM,生成人工智能,GPT".
- 两位评论员确定了前100篇论文,根据BIBLIO的指导方针提取了出版物细节,引文和研究主题.
主要成果:
- 排名前100的文章得到了14847次引用,平均每篇文章引用次数为148.47次.
- 美国领导贡献 (56篇文章),斯坦福大学是最多产的机构 (8篇文章).
- 研究主题集中在医学考试中的LLM绩效,知识综合和问答,在临床决策支持和药物发现方面取得了重大进展.
结论:
- 本分析提供了对医学领域高影响力LLM研究的核心概述.
- 这些发现强调了临床决策支持,药物发现和医学成像分析方面的进步.
- 未来的工作应侧重于未来的试验,提高LLM的可靠性,解决道德问题,并促进全球获取LLM工具.
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