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Understanding the Complexity of Heart Failure Risk and Treatment in Black Patients.理解黑人群体心力衰竭风险和治疗的复杂性。
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Kidney Disease Among African Americans: A Population Perspective.非裔美国人的肾脏病:从人群角度看。
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Trends in Health Disparities, Health Inequity, and Social Determinants of Health Research: A 17-Year Analysis of NINR, NCI, NHLBI, and NIMHD Funding.健康差异、健康不平等及健康研究的社会决定因素趋势:对美国国立护理研究院、国立癌症研究所、国立心肺血液研究所及国立少数族裔健康与健康不平等研究所17年资助情况的分析
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机器学习在医疗保健应用设计中的生物伦理原则:实现健康公正与健康公平

Bioethics Principles in Machine Learning-Healthcare Application Design: Achieving Health Justice and Health Equity.

作者信息

Fritz Roschelle L, Nguyen-Truong Connie Kim Yen, May Thomas, Wuestney Katherine, Cook Diane J

机构信息

Betty Irene Moore School of Nursing at UC Davis in Sacramento, CA and Affiliate Faculty at Washington State University, Nursing & Systems Science Department, College of Nursing in Vancouver, WA.

Washington State University, Department of Nursing and Systems Science, College of Nursing in Vancouver, WA.

出版信息

Harv Public Health Rev (Camb). 2024;79. doi: 10.54111/0001/aaaa1. Epub 2024 Aug 9.

DOI:10.54111/0001/aaaa1
PMID:39850650
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11756589/
Abstract

Health technologies featuring artificial intelligence (AI) are becoming more common. Some healthcare AIs are exhibiting bias towards underrepresented persons and populations. Although many computer scientists and healthcare professionals agree that eliminating or mitigating bias in healthcare AIs is needed, little information exists regarding how to operationalize bioethics principles like autonomy in product design and implementation. This short course is framed with a Social Determinants of Health lens and a health justice and health equity stance to support computer scientists and healthcare professionals in building and deploying ethical healthcare AI. In this short course we introduce the bioethics principle of autonomy in the context of human-centered design (Module 1) and share options for design thinking models, suggesting four activities to embed ethics principles during design (Module 2). We then discuss the importance of gaining the perspectives of diverse groups to minimize harm and support the fundamental human values of underrepresented persons in support of health equity and health justice ideals (Module 3).

摘要

以人工智能(AI)为特色的健康技术正变得越来越普遍。一些医疗保健人工智能对代表性不足的个人和人群表现出偏见。尽管许多计算机科学家和医疗保健专业人员都认为需要消除或减轻医疗保健人工智能中的偏见,但关于如何在产品设计和实施中践行诸如自主性等生物伦理原则的信息却很少。本短期课程以健康的社会决定因素视角以及健康正义和健康公平立场为框架,以支持计算机科学家和医疗保健专业人员构建和部署符合伦理的医疗保健人工智能。在本短期课程中,我们在以人为本的设计背景下介绍自主性的生物伦理原则(模块1),并分享设计思维模型的选项,提出在设计过程中融入伦理原则的四项活动(模块2)。然后,我们讨论获取不同群体观点的重要性,以尽量减少伤害,并支持代表性不足人群的基本人类价值观,以实现健康公平和健康正义的理想(模块3)。