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Artificial intelligence to advance acute and intensive care medicine

  • Department of Intensive Care Medicine
  • Amsterdam Medical Data Science (AMDS)
  • Amsterdam Cardiovascular Science (ACS)
  • Amsterdam Institute for Infection and Immunity (AII) and Amsterdam Cardiovascular Sciences (ACS)
  • Quantitative Data Analytics Group
  • Vrije Universiteit - Department of Computer Science
  • Faculty of Science
  • Vrije Universiteit Amsterdam
  • Amsterdam Public Health (APH)
  • University of Amsterdam
  • National Intensive Care Evaluation (NICE) Foundation

Research output: Contribution to journalReview articleAcademicpeer-review

279 Downloads (Pure)

Abstract

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.

Original languageEnglish
Pages (from-to)246-250
Number of pages5
JournalCurrent opinion in critical care
Volume30
Issue number3
Early online date14 Mar 2024
DOIs
Publication statusPublished - 1 Jun 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • artificial intelligence
  • generative artificial intelligence
  • machine learning
  • predictive models

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