缓解人工智能偏差在心血管保健中的风险
Ariana Mihan1, Ambarish Pandey2, Harriette Gc Van Spall3
1Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada.
The Lancet. Digital health
|August 30, 2024
概括
由于数据和实施问题,心血管健康中的人工智能 (AI) 可能会受到偏见,不成比例地伤害边缘化群体. 建议制定策略,以减轻人工智能对公平心血管护理的偏见.
科学领域:
- 心血管医学 心血管医学
- 人工智能的人工智能
- 健康 公平 卫生 公平
背景情况:
- 数字健康技术产生了对心血管保健中人工智能 (AI) 至关重要的数据.
- 在同质数据或不公平的医疗保健系统中训练的AI算法可以引入偏见.
- 在AI开发,测试,实施和后实施期间,偏见可能会出现.
研究的目的:
- 概述心血管健康中的AI应用.
- 在整个算法生命周期中讨论AI偏见来源.
- 为心血管疾病中的公平人工智能提出偏见缓解策略.
主要方法:
- 对心血管健康中人工智能应用的审查.
- 在AI算法开发和实施中分析偏差引入点.
- 确定减轻人工智能偏差的策略.
主要成果:
- 人工智能偏见可能导致误诊,错误的风险预测和不适当的治疗.
- 偏见的人工智能算法不成比例地影响边缘化人口群体.
- 在心血管保健中,偏见的人工智能的潜在危害是相当大的.
结论:
- 缓解人工智能偏见对于确保人工智能在心血管健康方面的公平利益至关重要.
- 在人工智能培训,测试和实施期间采取主动策略,可以减少偏见.
- 公平的AI部署可以帮助所有患有心血管疾病或有心血管疾病风险的个人平等地受益.
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