Artificial intelligence to advance acute and intensive care medicine.

Autor:	Biesheuvel LA; Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence (C4I), Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam Institute for Infection and Immunity (AII), Amsterdam Public Health (APH), Amsterdam UMC.; Quantitative Data Analytics Group, Department of Computer Science, Faculty of Science, Vrije Universiteit., Dongelmans DA; Department of Intensive Care Medicine, Amsterdam Public Health (APH), Amsterdam UMC, University of Amsterdam.; National Intensive Care Evaluation Foundation, Amsterdam, The Netherlands., Elbers PWG; Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence (C4I), Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam Institute for Infection and Immunity (AII), Amsterdam Public Health (APH), Amsterdam UMC.
Jazyk:	angličtina
Zdroj:	Current opinion in critical care [Curr Opin Crit Care] 2024 Jun 01; Vol. 30 (3), pp. 246-250. Date of Electronic Publication: 2024 Mar 22.
DOI:	10.1097/MCC.0000000000001150
Abstrakt:	Purpose of Review: This review explores recent key advancements in artificial intelligence for acute and intensive care medicine. As artificial intelligence rapidly evolves, this review aims to elucidate its current applications, future possibilities, and the vital challenges that are associated with its integration into emergency medical dispatch, triage, medical consultation and ICUs. Recent Findings: The integration of artificial intelligence in emergency medical dispatch (EMD) facilitates swift and accurate assessment. In the emergency department (ED), artificial intelligence driven triage models leverage diverse patient data for improved outcome predictions, surpassing human performance in retrospective studies. Artificial intelligence can streamline medical documentation in the ED and enhances medical imaging interpretation. The introduction of large multimodal generative models showcases the future potential to process varied biomedical data for comprehensive decision support. In the ICU, artificial intelligence applications range from early warning systems to treatment suggestions. Summary: Despite promising academic strides, widespread artificial intelligence adoption in acute and critical care is hindered by ethical, legal, technical, organizational, and validation challenges. Despite these obstacles, artificial intelligence's potential to streamline clinical workflows is evident. When these barriers are overcome, future advancements in artificial intelligence have the potential to transform the landscape of patient care for acute and intensive care medicine. (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu