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Considerations in the reliability and fairness audits of predictive models for advance care planning.预先护理计划预测模型可靠性和公平性审计的考量因素。
Front Digit Health. 2022 Sep 12;4:943768. doi: 10.3389/fdgth.2022.943768. eCollection 2022.
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Nat Mach Intell. 2022 Mar;4(3):189-191. doi: 10.1038/s42256-022-00465-9. Epub 2022 Mar 7.
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Ethics and society review: Ethics reflection as a precondition to research funding.伦理与社会评论:伦理反思是研究资助的前提。
Proc Natl Acad Sci U S A. 2021 Dec 28;118(52). doi: 10.1073/pnas.2117261118.
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Implementing Incentives and Rewards to Improve the Research Ecosystem.实施激励措施以改善研究生态系统。
JAMA Netw Open. 2021 Nov 1;4(11):e2138622. doi: 10.1001/jamanetworkopen.2021.38622.
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Responsible use of polygenic risk scores in the clinic: potential benefits, risks and gaps.临床中多基因风险评分的合理使用:潜在的获益、风险和差距。
Nat Med. 2021 Nov;27(11):1876-1884. doi: 10.1038/s41591-021-01549-6. Epub 2021 Nov 15.
6
A Typology of Existing Machine Learning-Based Predictive Analytic Tools Focused on Reducing Costs and Improving Quality in Health Care: Systematic Search and Content Analysis.基于机器学习的预测分析工具的分类学研究,旨在降低医疗成本和提高医疗质量:系统检索和内容分析。
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A framework for making predictive models useful in practice.一个使预测模型在实践中有用的框架。
J Am Med Inform Assoc. 2021 Jun 12;28(6):1149-1158. doi: 10.1093/jamia/ocaa318.
8
Dissecting racial bias in an algorithm used to manage the health of populations.剖析用于管理人群健康的算法中的种族偏见。
Science. 2019 Oct 25;366(6464):447-453. doi: 10.1126/science.aax2342.
9
Clinical use of current polygenic risk scores may exacerbate health disparities.现行多基因风险评分的临床应用可能会加剧健康差异。
Nat Genet. 2019 Apr;51(4):584-591. doi: 10.1038/s41588-019-0379-x. Epub 2019 Mar 29.
10
Beyond patchwork precaution in the dual-use governance of synthetic biology.超越合成生物学两用治理中的补丁式防范。
Sci Eng Ethics. 2013 Sep;19(3):1121-39. doi: 10.1007/s11948-012-9365-8. Epub 2012 Apr 26.

加强人工智能在生物医学领域的监管。

Stronger regulation of AI in biomedicine.

机构信息

Stanford Center for Biomedical Ethics, Stanford University, Stanford, CA, USA.

Department of Genetics, Stanford University, Stanford, CA, USA.

出版信息

Sci Transl Med. 2023 Sep 13;15(713):eadi0336. doi: 10.1126/scitranslmed.adi0336.

DOI:10.1126/scitranslmed.adi0336
PMID:37703349
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10977140/
Abstract

Regulatory agencies need to ensure the safety and equity of AI in biomedicine, and the time to do so is now.

摘要

监管机构需要确保人工智能在生物医学中的安全性和公平性,现在是采取行动的时候了。