How do experts classify sepsis cases for sepsis surveillance? Lessons learned from a Behavioural Artificial Intelligence Technology (BAIT) approach.

Journal: Journal of critical care
Published Date: Aug 8, 2025

Abstract

OBJECTIVES: To identify relevant objective variables for retrospective identification of 'suspected infection' and sepsis, using behavioural artificial intelligence technology (BAIT), and to explore the accuracy of this approach for sepsis surveillance.

Authors

  • Renée A M Tuinte
    Radboud University Medical Center, Department of Internal Medicine, Nijmegen, the Netherlands; Radboud University Medical Center, Radboud Community for Infectious Diseases (RCI), Nijmegen, the Netherlands. Electronic address: renee.tuinte@radboudumc.nl.
  • Nicolaas Heyning
    Councyl, Delft, the Netherlands.
  • Annebel Ten Broeke
    Councyl, Delft, the Netherlands.
  • Hugo R W Touw
    Radboud University Medical Center, Department of Intensive Care Medicine, Nijmegen, the Netherlands.
  • Jaap Ten Oever
    Radboud University Medical Center, Department of Internal Medicine, Nijmegen, the Netherlands; Radboud University Medical Center, Radboud Community for Infectious Diseases (RCI), Nijmegen, the Netherlands.
  • Jacobien J Hoogerwerf
    Radboud University Medical Center, Department of Internal Medicine, Nijmegen, the Netherlands; Radboud University Medical Center, Radboud Community for Infectious Diseases (RCI), Nijmegen, the Netherlands.

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