人工智能和医学教育的大型语言模型的关键节点和全球趋势的绘制:一项图书统计研究
Kaining Lu1,2,3,4, Shuben Sun1,2,3,4, Wanzhang Liu1,2,3,4
1Department of Urology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, 315010, People's Republic of China.
人工智能 (AI) 和大型语言模型 (LLM) 正在迅速推进医学教育. 图书测量分析揭示了关键趋势,像ChatGPT这样的主导研究领域,以及临床推理和虚拟现实等未经探索的主题.
科学领域:
- 医疗教育
- 人工智能
- 图书识别技术
背景情况:
- 人工智能 (AI) 和大型语言模型 (LLM) 正在对医学教育产生重大影响.
- 需要了解这个快速增长的研究领域的文献统计趋势.
研究的目的:
- 在医学教育中对AI和LLM进行文献分析.
- 确定主要趋势,有影响力的出版物和研究缺口.
主要方法:
- 来自Web of Science核心集合的547个出版物的图书统计分析.
- 使用CiteSpace和其他文献计量工具来分析出版物量,协作,引用和关键词.
主要成果:
- 美国,英国和中国在出版量方面处于领先地位.
- 聊天GPT和LLM是主要的研究主题,越来越关注护理教育,数字健康和医疗伦理.
- 临床推理,本科教育和虚拟现实被认为是尚未探索的领域.
结论:
- AI和LLM正在改变医学教育,
- 医学伦理学和培训方法等新兴领域正在发展.
- 在临床推理和虚拟现实应用等研究不足的领域存在重大研究机会.
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