基于人工智能的外科预测模型的伦理陷
Sara Ben Hmido1,2, Houssam Abder Rahim3, Boris Keller3
1Department of Surgery, Amsterdam University Medical Centers, Amsterdam, the Netherlands.
World journal of surgery
|September 4, 2025
概括
预测模型在手术中提供了显著的好处,但也带来了道德上的挑战. 谨慎开发和实施对于确保患者安全,公平和对手术人工智能的信任至关重要.
科学领域:
- 外科创新
- 医学伦理
- 医疗保健中的人工智能
背景情况:
- 手术中的预测模型旨在通过预测并发症和个性化治疗来增强临床护理.
- 尽管有潜在的好处,但将这些模型纳入实践带来了重大的伦理挑战.
- 伦理问题涉及整个模型生命周期,从数据收集到临床应用,影响所有利益相关者.
研究的目的:
- 识别和分析与外科预测模型相关的伦理挑战.
- 探索数据偏差,隐私泄露和算法不透明等风险.
- 提出应对策略和负责整合的道德框架.
主要方法:
- 在整个预测模型生命周期中审查伦理考虑.
- 风险分析包括数据集偏差,隐私侵犯和缺乏透明度.
- 确定减轻风险的策略,如检测销售和持续审计.
主要成果:
- 确定了关键风险:偏见的数据集,隐私侵犯,不透明的决策和潜在的外科医生失业.
- 重要的缓解策略包括标准化数据收集,并行开发和审计.
- 一个强调责任和以患者为中心的伦理框架至关重要.
结论:
- 在手术中整合预测模型需要技术专长和道德警.
- 未来临床医生的教育必须包括临床推理和道德意识.
- 将人工智能发展与以人为中心的价值观结合起来,
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