大型语言模型在临床护理中的应用和挑战:系统性审查
Jiaojiao Song1, Wenlong Liu, Yazhe Wang
1Author Affiliation: Digestive Endoscopy Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China.
Computers, informatics, nursing : CIN
|June 17, 2025
概括
大型语言模型 (LLM) 在决策支持和文档等领域提高临床护理效率和质量. 应对数据隐私和伦理等挑战是释放他们在护理方面的全部潜力的关键.
科学领域:
- 护理信息学 护理信息学
- 人工智能的人工智能
- 医疗保健服务研究 医疗服务研究
背景情况:
- 临床护理面临着越来越高的效率和质量的要求.
- 大型语言模型 (LLM) 为医疗保健挑战提供了潜在的解决方案.
- 在护理学LLMs的整合需要系统的评估.
研究的目的:
- 系统地审查临床护理中大型语言模型的当前状态.
- 确定与LLM在护理中的实施相关的未来前景和挑战.
- 提供关于应对已确定的挑战和未来发展方向的见解.
主要方法:
- 在遵守PRISMA指南的基础上进行系统审查.
- 在EMBASE,CINAHL,MEDLINE和科学网上进行全面的文献搜索.
- 包括2021年1月1日至2024年10月23日期间发表的15项符合条件的研究.
主要成果:
- 通过LLM,可以显著提高护理效率和质量.
- 关键应用包括临床决策支持,患者教育,文档和工作流程优化.
- 确定的挑战包括数据隐私,模型准确性和道德考虑.
结论:
- 士在临床护理方面显示出革命性的潜力,能够彻底改变临床护理实践.
- 克服与隐私,准确性和道德相关的挑战对于成功的采用至关重要.
- 未来的发展应该专注于安全,道德和有效地将LLMs纳入护理.
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