健康人工智能给残疾人带来了明显的危害和潜在的好处

IF 58.7 1区医学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

Nature Medicine Pub Date : 2025-01-14 DOI:10.1038/s41591-024-03432-6

Charles E. Binkley, Joel M. Reynolds, Andrew G. Shuman

引用次数: 0

摘要

相对于人工智能（AI）中存在偏见风险的其他群体，人们很少关注人工智能模型可能给残疾人带来的潜在危害和明显的好处。人工智能模型对残疾患者的预测可能至少在三个方面导致歧视：残疾患者在数据集中的代表性不足；她们在医疗服务方面历来受到歧视；用于预测生理脆弱的数据可能高估了残疾患者的脆弱程度。残疾人群体比一般人群要小，人工智能模型所使用的大多数医疗保健数据都来自非残疾患者。主要从非残疾患者的数据上训练的人工智能模型可以准确地预测这些患者的给定结果，但在应用于残疾患者时就失败了。此外，与残疾患者有关的健康数据可能缺失或不完整。在数据集中，由于代表性不足和误读而导致的偏见和歧视的可能性被很好地描述了1。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nature Medicine 医学-生化与分子生物学

CiteScore

100.90

自引率

0.70%

发文量

525

审稿时长

1 months

期刊介绍： Nature Medicine is a monthly journal publishing original peer-reviewed research in all areas of medicine. The publication focuses on originality, timeliness, interdisciplinary interest, and the impact on improving human health. In addition to research articles, Nature Medicine also publishes commissioned content such as News, Reviews, and Perspectives. This content aims to provide context for the latest advances in translational and clinical research, reaching a wide audience of M.D. and Ph.D. readers. All editorial decisions for the journal are made by a team of full-time professional editors. Nature Medicine consider all types of clinical research, including: -Case-reports and small case series -Clinical trials, whether phase 1, 2, 3 or 4 -Observational studies -Meta-analyses -Biomarker studies -Public and global health studies Nature Medicine is also committed to facilitating communication between translational and clinical researchers. As such, we consider “hybrid” studies with preclinical and translational findings reported alongside data from clinical studies.