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医学教育中人工智能生成的视频:系统审查

Yaara Artsi¹, Vera Sorin², Benjamin Glicksberg^3,4

¹Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel yaara.artsi77@gmail.com.

BMJ open quality

|December 22, 2025

概括

人工智能 (AI) 产生的视频显示了参与医学教育的潜力,但需要进一步验证. 目前的证据有限,凸显了这些新型工具对准确性和不一致的结果测量的担忧.

科学领域:

医疗教育技术技术医学教育
医疗保健中的人工智能
数字健康干预措施数字健康干预措施

背景情况:

新兴的人工智能 (AI) 产生的文本到视频工具正在被用于医学教育.
这些人工智能工具在学习者或患者教育中的有效性,准确性和安全性尚未得到充分证实.
本系统审查综合了医疗和患者教育中人工智能生成的视频工具的经验证据.

研究的目的:

系统地评估在医学教育和患者教育中使用人工智能 (AI) 产生的文本到视频工具的经验证据.
根据现有研究,评估这些AI工具的有效性,准确性和安全性.
确定当前研究中的差距,并为未来的使用提供建议.

主要方法:

在主要数据库 (MEDLINE/PubMed,Google Scholar,Scopus,Cochrane Review,Web of Science) 进行了全面的文献搜索,截至2025年1月.
包括评估人工智能生成的文本到视频用于医疗或患者教育的研究,报告定量和定性结果.
数据提取和选由两位审查员进行,遵循系统审查和元分析 (PRISMA) 准则的首选报告项目.

主要成果:

五项研究符合纳入标准,重点是患者教育 (4/5) 和医生培训 (1/5) 在眼科,整形外科,失足症康复和神经外科.
在眼科中,人工智能视频的准确性低于对照材料 (p<0.005). 然而,人工智能辅助的视频游戏改善了吞功能 (p<0.001) 在食障碍康复中.
在一项研究中,用户偏好人工智能视频化身而不是文字聊天机器人,但样本大小小小,结果措施异质,排除了元分析.

结论:

人工智能生成的视频可能会在某些医学教育环境中提高参与度和特定结果.
对准确性和不一致的测量持续存在的担忧凸显了进一步严格研究的必要性.
当前的人工智能视频工具可以补充,但不能取代传统的教育资源,直到非劣势被证明.

关键词:

人工智能的人工智能继续教育,持续的专业发展.教育教育教育教育教育教育.医学教育医学教育患者教育患者教育

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