医疗保健中的生成人工智能:对患者机构的挑战和伦理影响
Scott A Holmes1,2, Vanda Faria2,3,4, Eric A Moulton2,4,5
1Pediatric Pain Pathway Lab, Department of Anesthesia, Critical Care and Pain Medicine, Boston Children's Hospital/Harvard Medical School, Boston, MA, United States.
Frontiers in digital health
|July 3, 2025
概括
医疗保健中的生成人工智能引入了复杂的数据挑战. 确保人工智能驱动的医疗决策的问责制和透明度对于患者的安全和信任至关重要.
科学领域:
- 医疗保健人工智能的人工智能
- 医疗信息学 医疗信息学
- 生物伦理学生物伦理学
背景情况:
- 临床研究正在发展,超越了仅供人类使用的数据源.
- 人工智能 (AI) 方法在医疗保健研究和临床实践中越来越多地使用.
- 生成性AI引入了缺乏个人生活经验的新型数据类型.
研究的目的:
- 检查生成人工智能对医疗保健中的自我代理的影响.
- 讨论人工智能生成数据在医疗决策中的伦理考虑.
- 为医疗保健中负责任的人工智能整合提出未来方向.
主要方法:
- 对人工智能和医疗保健当前趋势的评论和讨论.
- 在生成数据的背景下分析自我代理的概念.
- 审查因数据源透明度问题对患者护理的潜在影响.
主要成果:
- 生成型人工智能挑战临床研究中的传统数据范式.
- 人工智能数据源缺乏透明度对患者护理构成风险.
- 自主代理的概念直接面临着人工智能的扩散.
结论:
- 在人工智能驱动的医疗保健中迫切需要问责制和透明度.
- 未来的战略必须确保人工智能补充,而不是破坏以人为中心的护理.
- 伦理框架对于导航人工智能在医学进步中的作用至关重要.
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