在ICU中数据驱动的护理质量:简要的审查
Giulliana M Moralez1,2, Filipe Amado1, Vincent X Liu3
1Department of Critical Care, D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil.
Critical care medicine
|September 19, 2025
概括
人工智能 (AI) 和机器学习 (ML) 在重症监护室 (ICU) 提供了改造潜力,以提高患者护理和运营效率. 成功的整合需要经过验证,透明的AI模型和临床医生的信任来克服实施挑战.
科学领域:
- 关键护理医学 关键护理医学
- 数据科学应用程序数据科学应用程序
- 医疗保健中的人工智能
背景情况:
- 人工智能 (AI) 和机器学习 (ML) 越来越被认为是重症监护医学的强大工具.
- 尽管有众多AI/ML模型的开发,但它们的日常整合到重症监护室 (ICU) 实践中仍然有限.
- 本综述探讨了人工智能和数据科学在提高ICU安全,质量,临床过程和管理方面的作用.
研究的目的:
- 检查人工智能和数据科学在重症监护中的作用.
- 突出对安全,质量保证,临床过程和ICU管理的贡献.
- 确定在ICU中实施AI驱动解决方案的机遇和挑战.
主要方法:
- 在PubMed中使用关键词进行文献搜索:AI,ML,ICU管理,临床决策支持,预测分析.
- 将AI/ML的原始研究,评论,信件和评论纳入ICU质量和性能中.
- 将关键发现综合成一个结构化的叙事审查.
主要成果:
- 人工智能和机器学习利用临床数据来评估ICU的性能,识别风险因素,优化工作流程和预测不良事件.
- 机器学习模型在改善临床决策和ICU管理方面显示出前景.
- 现实世界的实施面临挑战,包括需要严格的验证和临床医生采用.
结论:
- 人工智能和机器学习具有重大潜力,可以彻底改变ICU管理.
- 成功采用人工智能取决于可验证,可互操作和可解释的模型,这些模型可以培养临床医生的信任.
- 在ICU中推进AI需要一种多学科的方法,以找到适应性,透明性和临床价值的解决方案.
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