对FDA批准的AI医疗器械报告漏洞的范围审查
Vijaytha Muralidharan1, Boluwatife Adeleye Adewale2,3, Caroline J Huang4
1Department of Dermatology, Stanford University School of Medicine, Stanford, CA, 94304, USA. vmurali5@stanford.edu.
NPJ digital medicine
|October 3, 2024
概括
美国食品和药物管理局批准的AI/ML医疗设备对患者人口统计和社会经济因素的报道很差. 这种缺乏数据的风险加剧了医疗保健中的健康差异和算法偏见.
科学领域:
- 医疗信息学 医疗信息学
- 健康 公平 卫生 公平
- 监管科学 监管科学
背景情况:
- 医疗保健中的人工智能和机器学习 (AI/ML) 模型有可能加剧现有的健康偏见.
- 监管监督对于评估AI/ML医疗器械在临床实践中的安全性和有效性至关重要.
研究的目的:
- 进行FDA批准的AI/ML支持医疗器械的范围审查.
- 在1995-2023年期间检查设备批准的透明度,安全报告和社会人口统计代表性.
主要方法:
- 对692个FDA批准的AI/ML支持医疗器械进行范围审查.
- 对有关种族/种族,社会经济地位,年龄,性能研究,出版链接和市场后监测的报告数据的分析.
主要成果:
- 只有3.6%的批准报告了种族/种族;99.1%缺乏社会经济数据;81.6%遗漏了受试者的年龄.
- 不到一半 (46.1%) 提供了全面的绩效结果,只有1.9%与出版物相关.
- 仅有9.0%的研究包括了市场后监测的前性研究.
结论:
- 美国食品和药物管理局对AI/ML医疗器械的报告不一致,对人口统计和社会经济特征的报告显著不足.
- 这种数据差距增加了算法偏差的风险,并扩大了健康差距.
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