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Documentation in long-term care facilities and home healthcare settings is crucial for ensuring continuous, coordinated, and comprehensive care for patients. Each setting has its specific documentation processes and tools:
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相关实验视频

Updated: Jan 9, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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在护理实践中使用大型语言模型驱动的代理:范围审查.

Xinglin Zheng1, Huina Zou1, Linjing Wu1

  • 1Nursing Department, Xiamen Cardiovascular Hospital, Xiamen University, Xiamen, China.

International journal of nursing sciences
|December 10, 2025
PubMed
概括

护理中的大型语言模型驱动代理 (LLMDA) 提高了护理的准确性和效率. 应对伦理和技术挑战对于其成功的临床实施和未来的研究至关重要.

关键词:
代理人 代理人 代理人伦理上的挑战 伦理上的挑战大型语言模型.多个代理合作的合作.护理 护理 护理

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科学领域:

  • 护理信息学 护理信息学
  • 医疗保健中的人工智能
  • 数字健康数字健康

背景情况:

  • 集成先进的人工智能,特别是大型语言模型驱动代理 (LLMDAs),在护理实践中提供了一个变革性的机会.
  • 了解目前在护理领域的LLMDA的现状对于指导未来的技术进步和临床应用至关重要.

研究的目的:

  • 系统地分析LLMDA在护理中的技术框架,应用场景和结果.
  • 识别和总结与LLMDA在护理中的实施相关的伦理,技术和实际挑战.

主要方法:

  • 根据JBI的指导方针进行了范围审查.
  • 在五个主要数据库 (PubMed,Embase,Web of Science,APA PsycNet,Cochrane Library) 进行了搜索,搜索到2025年9月9日之前发表的英语研究.
  • 符合条件的研究经过了标题/摘要选,随后由两名审稿人进行独立的全文评估.

主要成果:

  • 包括来自9个国家的25项研究 (2023-2025年),重点是中国和美国.
  • 技术架构包括在临床,家庭和社区护理环境中应用的协作,增强和交互模型.
  • 在提高诊断准确性,资源分配和患者体验方面,LLMDAs显示出潜力,同时突出了数据隐私,内容可靠性和责任归属方面的挑战.

结论:

  • 在护理保健中,LLMDAs代表了智能转型的新范式.
  • 这些药物显示出提高临床决策,护理提供效率和患者满意度的巨大潜力.
  • 克服现有的伦理,技术和实际障碍对于广泛的临床采用至关重要.