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Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22

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Peer-reviewed

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Abstract

Artificial Intelligence (AI) is rapidly transforming the landscape of critical care, offering opportunities for enhanced diagnostic precision and personalized patient management. However, its integration into ICU clinical practice presents significant challenges related to equity, transparency, and the patient-clinician relationship. To address these concerns, a multidisciplinary team of experts was established to assess the current state and future trajectory of AI in critical care. This consensus identified key challenges and proposed actionable recommendations to guide AI implementation in this high-stakes field. Here we present a call to action for the critical care community, to bridge the gap between AI advancements and the need for humanized, patient-centred care, ensuring the transition to personalized medicine while maintaining equitable and unbiased decision-making, fostering the development of a collaborative research network across ICUs, emergency departments, and operating rooms to promote data sharing and harmonization, and addressing the necessary educational and regulatory shifts required for responsible AI deployment. Integrating AI into critical care demands coordinated efforts among clinicians, patients, industry leaders, and regulators to ensure patient safety and maximize societal benefit. The recommendations outlined here provide a foundation for the ethical and effective implementation of AI in critical care medicine.

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Keywords

Journal Title

Critical Care

Conference Name

Journal ISSN

1364-8535
1364-8535

Volume Title

Publisher

Springer Science and Business Media LLC

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Except where otherwised noted, this item's license is described as Attribution 4.0 International