算法划分:对人工智能驱动的医疗保健种族差异的系统审查
Syed Ali Haider1, Sahar Borna1, Cesar A Gomez-Cabello1
1Division of Plastic Surgery, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL, 32224, USA.
Journal of racial and ethnic health disparities
|December 18, 2024
概括
医疗保健中的人工智能 (AI) 由于偏见的数据和算法,加剧了种族差异. 解决这个问题需要道德的人工智能开发,偏见检测和医生监督,以确保公平的患者结果.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能伦理学 人工智能伦理学
- 健康 公平 卫生 公平
背景情况:
- 人工智能 (AI) 的部署引发了人们对延续差距的担忧.
- 人工智能的性能取决于算法质量和训练数据完整性.
- 本综述侧重于医疗保健中人工智能的种族差异.
研究的目的:
- 系统地审查和分析人工智能在医疗保健中造成的种族差异.
- 调查人工智能部署对少数群体健康结果的影响.
主要方法:
- 在六个数据库 (PubMed,Scopus,IEEE,Google Scholar,EMBASE,Cochrane) 进行系统搜索,截至2023年10月3日.
- 包括同行评审的英语文章 (2013-2023) 关于AI在医疗保健中的种族偏见.
- 排除医疗保健以外的研究,非种族偏见,信件和意见.
主要成果:
- 30篇文章符合资格标准,表明人工智能加剧了种族差异,特别是在黑人和西班牙裔人口中.
- 确定的原因包括有偏见的数据,算法设计,不公平的部署和系统不平等.
- 研究异质性有限的元分析.
结论:
- 加强的伦理考虑和监管框架对于医疗保健中的AI至关重要.
- 偏见检测工具,缓解策略和医生监督是必不可少的.
- 人工智能必须被利用来减少,而不是扩大医疗保健结果差异.
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