大型语言模型能否促进在临床环境中有效实施护理流程?
1Nursing Department, Department of Neurosurgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China.
BMC nursing
|April 8, 2025
概括
大型语言模型 (LLM) 对生成护理诊断和护理计划充满希望,可与黄金标准相提并论. 为了有效的临床整合,需要进一步的研究.
科学领域:
- 护理信息学 护理信息学
- 医疗保健中的人工智能
- 临床决策支持 临床决策支持
背景情况:
- 关于人工智能产生的护理诊断和护理计划的质量存在争论.
- 之前的研究主要使用了ChatGPT,限制了对比分析.
研究的目的:
- 通过各种大型语言模型 (LLM) 快速框架生成的护理诊断和计划进行评估.
- 评估LLM在护理实践中的临床适用性.
主要方法:
- 开发了一个结构化的护理评估模板和一个采用各种技术的快速框架.
- 评估了ERNIE Bot 4.0和Moonshot AI的护理诊断和护理计划.
- 评估了LLM产生的内容的临床实用性.
主要成果:
- 由LLM生成的护理诊断与黄金标准保持一致.
- 结构化模板有效地捕获了神经外科患者数据.
- 促使技术增强了LLM的概括能力.
结论:
- 在临床护理应用中,LLM显示出潜在的潜力.
- 在将LLM辅助护理整合到临床工作流程中仍然存在挑战.
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