Barea Mendoza Jesús Abelardo, Valiente Fernandez Marcos, Pardo Fernandez Alex, Gómez Álvarez Josep
UCI de Trauma y Emergencias. Servicio de Medicina Intensiva. Hospital Universitario 12 de Octubre. Instituto de Investigación Hospital 12 de Octubre, Spain.
UCI de Trauma y Emergencias. Servicio de Medicina Intensiva. Hospital Universitario 12 de Octubre. Instituto de Investigación Hospital 12 de Octubre, Spain.
Med Intensiva (Engl Ed). 2025 Mar;49(3):154-164. doi: 10.1016/j.medine.2024.04.002. Epub 2024 Apr 26.
Intensive Care Units (ICUs) have undergone enhancements in patient safety, and artificial intelligence (AI) emerges as a disruptive technology offering novel opportunities. While the published evidence is limited and presents methodological issues, certain areas show promise, such as decision support systems, detection of adverse events, and prescription error identification. The application of AI in safety may pursue predictive or diagnostic objectives. Implementing AI-based systems necessitates procedures to ensure secure assistance, addressing challenges including trust in such systems, biases, data quality, scalability, and ethical and confidentiality considerations. The development and application of AI demand thorough testing, encompassing retrospective data assessments, real-time validation with prospective cohorts, and efficacy demonstration in clinical trials. Algorithmic transparency and explainability are essential, with active involvement of clinical professionals being crucial in the implementation process.
重症监护病房（ICU）在患者安全方面已有改进，人工智能（AI）作为一种颠覆性技术出现，带来了新的机遇。虽然已发表的证据有限且存在方法学问题，但某些领域显示出前景，如决策支持系统、不良事件检测和处方错误识别。AI在安全方面的应用可能追求预测或诊断目标。实施基于AI的系统需要确保安全辅助的程序，应对包括对此类系统的信任、偏差、数据质量、可扩展性以及伦理和保密性考虑等挑战。AI的开发和应用需要进行全面测试，包括回顾性数据评估、对前瞻性队列的实时验证以及在临床试验中证明疗效。算法的透明度和可解释性至关重要，临床专业人员的积极参与在实施过程中至关重要。
