公共卫生 公共卫生
Krista Y Chen1, Joseph S Ross2, Adam B Cohen2
1Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Alzheimer's & dementia : the journal of the Alzheimer's Association
|December 23, 2025
概括
对阿尔茨海默病和相关痴呆症 (ADRD) 的AI/ML设备的有限数据透明度阻碍了知情的临床使用,并可能加剧少数群体患者的健康差异.
科学领域:
- 医疗器械监管法规 医疗器械监管法规
- 医疗保健中的人工智能
- 神经退行性疾病诊断神经退行性疾病诊断
背景情况:
- 准确检测阿尔茨海默病和相关痴呆症 (ADRD) 对患者的护理和治疗至关重要.
- 人工智能/ML医疗设备对ADRD诊断有前途,但需要透明度.
- 人们对AI/ML设备的准确性和可能加剧健康差距存在担忧.
研究的目的:
- 评估透明度和支持FDA批准的ADRD的AI/ML设备的数据.
- 评估这些设备的培训和验证数据集的可用性和质量.
- 发现ADRD中使用的AI/ML设备的人口报告中的差距.
主要方法:
- 自2015年以来,系统地搜索FDA数据库和文献,寻找AI/ML设备,这些设备已被清除ADRD.
- 审查FDA批准摘要和同行评审文章的数据可用性和质量.
- 提取有关监管途径,指示和数据集特征 (设计,大小,人口统计) 的数据.
主要成果:
- 自2015年以来,有24个AI/ML设备被FDA批准用于ADRD;大多数通过510(k) 途径.
- 指示包括大脑结构量化,功能测试和粉样蛋白沉积.
- 在FDA摘要和文献中,对培训/验证数据和患者人口统计数据 (特别是种族/种族) 的报告有限.
结论:
- 在支持FDA批准的ADRDAI/ML设备的证据中存在显著的差距.
- 数据的有限透明度限制了临床医生的知情决策.
- 这些限制引发了对患者,特别是种族/少数民族的潜在负面影响的担忧.
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