从承诺到实践:人工智能在重症监护中的路线图
Geoffray Agard1, Sami Hraiech2, Tobias Gauss3
1Department of Intensive Care Medicine, Assistance Publique-Hôpitaux de Marseille (AP-HM), Hôpital Nord, Marseille, France; Aix-Marseille University, Faculty of Medicine, Center for Studies and Research on Health Services and Quality of Life (CERESS), EA 3279, 13005 Marseille, France; Laboratory of Computer Science and Systems (LIS), UMR 7020 CNRS / Aix-Marseille University, Saint Jérôme Campus - Polytech Building, Marseille, France.
Journal of critical care
|September 18, 2025
概括
在重症监护室 (ICU) 的人工智能 (AI) 显示出希望,但面临着有限的临床转化. 拟议的路线图强调了谨慎,以人为中心的实施,而不是为安全的AI采用快速取得突破.
科学领域:
- 医疗信息学 医疗信息学
- 关键护理医学 关键护理医学
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 在医学领域正在迅速发展,特别是在重症监护室 (ICU),因为数据密度高,患者易受伤害.
- 尽管有许多概念验证研究,但ICU中AI工具的临床翻译仍然很少,只有不到2%的前性评估.
研究的目的:
- 讨论关于将人工智能整合到重症监护机构的路线图.
- 突出在ICU采用人工智能的逐步,与风险一致的框架的重要性.
- 强调超越模型表现的基本价值观,包括公平性,可解释性和问责制.
主要方法:
- 讨论Workum等人提出的路线图. 为了在重症监护中整合AI.
- 分析实际挑战,包括数据互操作性,基础设施,治理和责任.
- 强调人工智能实施中的公平性,可解释性和问责制等价值观.
主要成果:
- 在ICU中采用人工智能的障碍是周围的生态系统 (数据质量,监管,信任),而不是单独的算法.
- 路线图倡导谨慎的方法,从低风险的应用开始.
- 在高风险决策支持之前,对临床益处的严格评估至关重要.
结论:
- 人工智能在ICU的真正潜力在于仔细,以证据为基础,以人为中心的实施.
- 成功整合人工智能需要对基础设施和跨学科合作进行投资.
- 谨慎的进展和严格的评估对于实现人工智能在重症监护中的好处至关重要.
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