了解人工智能中的偏见:从实践的角度来看
Melissa A Davis1, Ona Wu2, Ichiro Ikuta3
1From Yale University (M.A.D., M.H.J.), New Haven, Connecticut Melissa.a.davis@yale.edu.
AJNR. American journal of neuroradiology
|December 20, 2023
概括
神经放射学中的人工智能 (AI) 需要对健康公平偏见进行仔细评估. 这种观点引导神经放射学家评估人工智能工具,以确保公平的放射性护理.
科学领域:
- 神经辐射学神经辐射学
- 人工智能的人工智能
- 健康 公平 卫生 公平
背景情况:
- 美国神经辐射学会 (ASNR) 多样性和包容性委员会主办了一场关于人工智能 (AI) 在医疗保健中的偏见的网络研讨会.
- 了解和减轻人工智能工具中的偏见对于确保公平的放射性护理至关重要.
- 神经放射学家必须参与不断发展的AI技术,以保持持续的学习和道德实践.
研究的目的:
- 从ASNR网络研讨会中提取关于神经放射学中人工智能偏见的关键概念.
- 为神经放射学家提供一个框架来评估人工智能工具中的健康公平相关偏见.
- 通过临床工作流程示例,探索AI对公平放射治疗的影响.
主要方法:
- 来自ASNR网络研讨会的主要讨论点的提炼.
- 开发一个框架来评估AI工具的健康公平偏见.
- 介绍了AI在神经放射学中的临床工作流实施示例.
主要成果:
- 确定了解决神经放射学家对人工智能偏见的重要性.
- 为开发评估AI偏见的框架提供了见解.
- 强调了人工智能对公平放射性护理的潜在影响.
结论:
- 神经放射学家需要积极评估AI工具的潜在偏见.
- 结构化的框架对于评估人工智能应用中的健康公平至关重要.
- 与人工智能互动对于推进放射治疗中的公平实践至关重要.
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