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

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Bibliographic Details
Title: How do experts classify sepsis cases for sepsis surveillance? Lessons learned from a Behavioural Artificial Intelligence Technology (BAIT) approach.
Authors: Tuinte RAM; 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., Heyning N; Councyl, Delft, the Netherlands., Ten Broeke A; Councyl, Delft, the Netherlands., Touw HRW; Radboud University Medical Center, Department of Intensive Care Medicine, Nijmegen, the Netherlands., Ten Oever J; Radboud University Medical Center, Department of Internal Medicine, Nijmegen, the Netherlands; Radboud University Medical Center, Radboud Community for Infectious Diseases (RCI), Nijmegen, the Netherlands., Hoogerwerf JJ; Radboud University Medical Center, Department of Internal Medicine, Nijmegen, the Netherlands; Radboud University Medical Center, Radboud Community for Infectious Diseases (RCI), Nijmegen, the Netherlands.
Source: Journal of critical care [J Crit Care] 2026 Feb; Vol. 91, pp. 155214. Date of Electronic Publication: 2025 Aug 08.
Publication Type: Journal Article
Journal Info: Publisher: W.B. Saunders Country of Publication: United States NLM ID: 8610642 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1557-8615 (Electronic) Linking ISSN: 08839441 NLM ISO Abbreviation: J Crit Care Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1557-8615
DOI:10.1016/j.jcrc.2025.155214