在临床护理中获取增强生成的伦理要求:对负责任的人工智能使用的观点
Xinyi Tu1,2, Chenghao Shi1, Peilin Qian3
1Department of Nursing, The Second Affiliated Hospital of Zhejiang University School of Medicine, No. 88 Jiefang Road, Shangcheng District, Hangzhou, Zhejiang, 310009, China, 86 13867466291, 86 0571-87787013.
JMIR medical informatics
|January 9, 2026
概括
检索增强生成 (RAG) 系统为护理中的大型语言模型提供实时知识访问. 负责任的实施需要解决伦理风险,以确保患者安全和护理质量.
科学领域:
- 医疗保健中的人工智能
- 临床护理信息学 临床护理信息学
- 医学伦理 医学伦理
背景情况:
- 检索增强生成 (RAG) 通过实时的外部知识增强了大型语言模型 (LLM).
- 在医学研究和临床环境中,RAG的采用正在增加.
- 在患者护理中实施RAG时,道德考虑至关重要.
研究的目的:
- 探索RAG系统在临床护理中的伦理要求.
- 检查RAG增强的LLM在护理实践中的伦理风险.
- 提出关于在医疗保健中负责实施RAG的指导方针.
主要方法:
- 在护理的RAG中对伦理考虑的结构化分析.
- 审查关键原则:准确性,公平性,透明度,问责制和人类监督.
- 讨论数据治理和可解释的AI (XAI) 技术.
主要成果:
- 在临床护理环境中,RAG系统带来了伦理挑战.
- 确保准确性,公平性,透明度和问责制至关重要.
- 人类监督对于安全有效的RAG使用至关重要.
结论:
- 强大的数据治理,XAI和持续监测对于负责任的RAG实施至关重要.
- 医疗保健专业人员,人工智能开发人员和政策制定者之间的合作是必要的.
- 包括RAG在内的AI可以支持患者安全,减少差异,提高护理质量.
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