算法个人公平和医疗保健:一个范围审查
Joshua W Anderson1, Shyam Visweswaran1,2
1Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA.
medRxiv : the preprint server for health sciences
|April 8, 2024
概括
算法个人公平性确保相似的人得到相似的待遇,这对于减轻医疗保健AI偏见至关重要. 研究表明,这个领域正在发展,但需要在医疗保健环境中进行更全面的应用和评估.
科学领域:
- 计算机科学 计算机科学
- 医疗信息学 医疗信息学
- 伦理学 伦理学 伦理学
背景情况:
- 人工智能 (AI) 和统计算法越来越多地用于医疗保健.
- 这些算法可以延续或放大现有的偏见,导致临床护理中的差异.
- 算法公平,特别是个人公平 (同样对待相似的人),对于公平的医疗保健至关重要.
研究的目的:
- 进行对算法个人公平性研究的范围审查.
- 了解医疗保健中的个人公平的当前指标,方法和应用.
- 确定差距和未来的研究方向,以实现医疗保健算法的公平性.
主要方法:
- 在PubMed,ACM数字图书馆和IEEE Xplore进行了系统的文献搜索.
- 包括2013年1月至2023年9月期间发表的文章,重点关注算法个人公平性,偏见缓解和医疗保健应用.
- 30篇相关文章被选中用于数据提取和合成.
主要成果:
- 确定的主要主题包括公平的哲学基础,个人公平指标和缓解策略.
- 审查还探讨了个人和团体公平,联合公平指标和相关软件工具之间的相互作用.
- 记录了医疗保健中的个人公平性在各种子主题中的应用.
结论:
- 尽管最近取得了进展,但在医疗保健领域对算法个人公平性的研究和应用仍处于起步阶段.
- 需要进一步进行全面的研究,才能在临床环境中充分实施和评估个人公平原则.
- 通过个人公平来解决算法偏见对于促进公平的医疗保健结果至关重要.
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