Early sepsis prediction in the emergency department using machine learning
Machine learning models using routinely available ED data were associated with improved predictive performance of organ injury and 30-day mortality in early sepsis compared to conventional scoring systems, highlighting their potential for clinical decision support.
Authors
- Raymond J. van Wijk (ORCID: https://orcid.org/0000-0002-2106-7699)
- Sunil B. Nagaraj (ORCID: https://orcid.org/0000-0002-6409-4101)
- Jan C. ter Maaten (ORCID: https://orcid.org/0000-0002-0353-4011)
- Hjalmar R. Bouma (ORCID: https://orcid.org/0000-0003-1032-321X)
Institutions
- The University of Western Australia (AU)
Publication Details
- Journal
- The American Journal of Emergency Medicine
- Published
- 2025-09-22
- DOI
- https://doi.org/10.1016/j.ajem.2025.09.034
- Citations
- 1
- Primary Topic
- Sepsis Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.35