Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22
Name
13054_2025_Article_5532.pdf
Size
2.28 MB
Format
Adobe PDF
Checksum (MD5)
def472cd435ae8e68d2a4b5faad64e39
Author(s)
Cecconi, Maurizio
Greco, Massimiliano
Shickel, Benjamin
Angus, Derek C.
Bailey, Heatherlee
Bignami, Elena
Calandra, Thierry
Celi, Leo A.
Einav, Sharon
Elbers, Paul
Date Issued
July 8, 2025
Journal
Critical Care
Publisher
BioMed Central
Citation
Cecconi, M., Greco, M., Shickel, B. et al. Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22. Crit Care 29, 290 (2025).
Version
Final published version
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. Our goal is to ensure a smooth transition to personalized medicine while, (1) maintaining equitable and unbiased decision-making, (2) fostering the development of a collaborative research network across ICUs, emergency departments, and operating rooms to promote data sharing and harmonization, and (3) addressing the necessary educational and regulatory shifts required for responsible AI deployment. AI integration 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.
MIT Department
Harvard--MIT Program in Health Sciences and Technology. Laboratory for Computational Physiology
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivatives
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DOI of Published Version
https://doi.org/10.1186/s13054-025-05532-2
