人工智能是如何改变医学教育的:图书识别分析
Youyang Wang1, Chuheng Chang2, Wen Shi3
1Department of General Practice (General Internal Medicine), Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
人工智能 (AI) 正在改变医学教育,转向生成性AI. 需要进一步的研究来整合人工智能,让教育工作者和学生参与未来的进步.
科学领域:
- 医学教育 医学教育
- 人工智能的人工智能
- 图书统计学 图书统计学
背景情况:
- 人工智能 (AI) 在医学教育中的整合正在加速.
- 人工智能承诺先进的辅导和课程改革,但面临着不准备和社区焦虑.
- 医学领域的基础人工智能已经显著发展,新的研究正在迅速出现.
研究的目的:
- 系统地分析研究趋势和人工智能医疗教育的未来方向.
- 通过参考文献分析来确定时间轨迹和该领域的关键发展.
主要方法:
- 系统地对Web of Science和Scopus (2000-2024) 的出版物进行文献计量分析.
- 使用信息检索,协作分析和引文爆发检测.
- 通过k-means集群检查的期刊和作者影响,研究趋势和引用谱系.
主要成果:
- 出版率在2021年后显著增加,从2019年开始进行基础工作.
- 研究从计算机辅助学习转向生成性AI平台.
- 人工智能应用正在从本科扩展到研究生和继续医学教育,生成人工智能和传统人工智能研究之间的集成有限.
结论:
- 需要进行跨学科研究,将生成人工智能与基础医疗人工智能相结合.
- 必须让医学教育工作者和学生参与人工智能开发过程.
- 未来的研究应该优先考虑理论框架和合作项目,以建立一个连贯的知识基础.
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