Health Equity and Artificial Intelligence in Nephrology.
作者信息
Engel Hercz Adam, Nicholas Susanne B, Bui Alex A T, Norris Keith C
机构信息
David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, California.
School of Medicine, Trinity College Dublin, The University of Dublin, Dublin, Ireland.
出版信息
Clin J Am Soc Nephrol. 2025 Apr 1;20(4):585-587. doi: 10.2215/CJN.0000000673. Epub 2025 Jan 28.
Abstract
摘要
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本文引用的文献
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Guidance for unbiased predictive information for healthcare decision-making and equity (GUIDE): considerations when race may be a prognostic factor.医疗保健决策与公平性的无偏预测信息指南（GUIDE）：种族可能成为预后因素时的考量
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Enhancing Clinical Decision Support in Nephrology: Addressing Algorithmic Bias Through Artificial Intelligence Governance.增强肾脏病学临床决策支持：通过人工智能治理解决算法偏差。
Am J Kidney Dis. 2024 Dec;84(6):780-786. doi: 10.1053/j.ajkd.2024.04.008. Epub 2024 Jun 6.
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Generalizability of an acute kidney injury prediction model across health systems.急性肾损伤预测模型在不同卫生系统中的可推广性。
Nat Mach Intell. 2022 Dec;4(12):1121-1129. doi: 10.1038/s42256-022-00563-8. Epub 2022 Dec 1.
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Five sources of bias in natural language processing.自然语言处理中偏见的五个来源。
Lang Linguist Compass. 2021 Aug;15(8):e12432. doi: 10.1111/lnc3.12432. Epub 2021 Aug 20.
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Hidden in Plain Sight - Reconsidering the Use of Race Correction in Clinical Algorithms.隐匿于众目睽睽之下——重新审视临床算法中种族校正的应用
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Structural racism in precision medicine: leaving no one behind.精准医学中的结构性种族主义：不落下任何人。
BMC Med Ethics. 2020 Feb 19;21(1):17. doi: 10.1186/s12910-020-0457-8.
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Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data.利用电子健康记录数据的机器学习算法中的潜在偏差。
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