医疗成像中的人工智能的伦理考虑:数据收集,开发和评估
Jonathan Herington1, Melissa D McCradden2, Kathleen Creel3
1Department of Health Humanities and Bioethics and Department of Philosophy, University of Rochester, Rochester, New York.
概括
核成像中的人工智能 (AI) 在数据处理,模型培训和临床应用方面提出了伦理挑战. 提供建议,以减轻有关隐私,数据质量,公平性和透明度的风险,以使患者受益.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 生物伦理学生物伦理学
背景情况:
- 人工智能 (AI) 越来越多地集成到核成像中.
- 这种整合在整个AI生命周期中引入了复杂的伦理考虑.
- 确保健康正义需要解决这些道德方面的问题.
研究的目的:
- 识别和分析与核成像中的AI相关的主要伦理风险.
- 为减轻这些已识别的风险提供初步建议.
- 为人工智能驱动医疗设备开发人员提供指导.
主要方法:
- 借鉴医学和研究伦理学既定的原则.
- 与核医学和分子成像学会的人工智能工作组进行商.
- 确定四个主要的伦理风险类别.
主要成果:
- 确定了四个主要的伦理风险:数据主体隐私,数据质量和模型有效性,对边缘化群体的公平性以及临床绩效的透明度.
- 这些风险在各个阶段表现出来:数据收集,模型培训/验证和临床使用.
- 为降低风险提出了初步建议.
结论:
- 解决伦理挑战对于负责地在核成像中实施人工智能至关重要.
- 缓解与隐私,质量,公平和透明度相关的风险对于患者和人口的福祉至关重要.
- 为了开发人工智能驱动的医疗设备,需要积极的道德考虑.
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