人工智能在居留申请评估中的使用-一个范围审查
Maxwell D Sumner1, T Clark Howell2, Alexandria L Soto3
1is an MD/MBA Candidate, Duke University School of Medicine, Durham, North Carolina, USA.
Journal of graduate medical education
|June 18, 2025
概括
人工智能 (AI) 正在探索居住申请选,但缺乏指导方针. 一项审查发现,人工智能模型在很大程度上未能探索或报告潜在的偏见,突出了公平和报告标准化的需要.
科学领域:
- 医学教育 医学教育
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 居住计划正在探索人工智能 (AI) 进行应用选.
- 目前对于在这种情况下使用人工智能方法没有标准化的指导方针.
研究的目的:
- 进行人工智能模型开发和应用在居留/奖学金选择中的范围审查.
- 评估AI模型的开发和应用中是否探索了偏见.
主要方法:
- 根据PRISMA-ScR指南进行范围审查.
- 在MEDLINE,Embase和Scopus数据库 (开始至2023年9月29日) 进行系统的文献搜索.
- 从包含的研究中提取数据和综合发现.
主要成果:
- 12项研究符合纳入标准,主要使用人工智能进行面试预测或排名 (75%).
- 在25%的研究中,自然语言处理被用来评估推信.
- 虽然大多数研究都提到偏见 (75%),但很少有人明确模拟或检查人口因素 (25%).
结论:
- 有限的研究存在于人工智能在居住选择,偏见在很大程度上没有解决.
- 在人工智能应用审查研究中,对偏见和公平性进行标准化报告至关重要.
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