Development and validation of an interpretable machine learning model for retrospective identification of suspected infection for sepsis surveillance: a multicentre cohort study
Authors
Konstantin Föhse (ORCID: https://orcid.org/0000-0002-4708-6943)
Mihai Gheorghe Netea (ORCID: https://orcid.org/0000-0003-2421-6052)
Jaap ten Oever (ORCID: https://orcid.org/0000-0003-2397-0125)
Jacobien J. Hoogerwerf (ORCID: https://orcid.org/0000-0001-9957-3703)
Renée A M Tuinte (ORCID: https://orcid.org/0000-0003-4225-9400)
Hjalmar R. Bouma (ORCID: https://orcid.org/0000-0003-1032-321X)
Bram T. Knoop
Katrijn Van Deun (ORCID: https://orcid.org/0000-0002-2271-793X)
Tamar J. van der Aart (ORCID: https://orcid.org/0000-0002-1518-8603)
Luuk P J Smolenaers
Institutions
University Medical Center Groningen (NL)
Goethe-Institute United Kingdom (GB)
University of Bonn (DE)
Radboud University Nijmegen (NL)
University of Groningen (NL)
Tilburg University (NL)
Radboud University Medical Center (NL)
Radboud Institute for Molecular Life Sciences (NL)
Development and validation of an interpretable machine learning model for retrospective identification of suspected infection for sepsis surveillance: a multicentre cohort study
Konstantin Föhse, Mihai Gheorghe Netea, Jaap ten Oever, Jacobien J. Hoogerwerf et al.
Citations
1 citations
Journal
EClinicalMedicine
Topics
Sepsis Diagnosis and Treatment
Field-Weighted Citation Impact (FWCI)
1.35
article
Development and validation of an interpretable machine learning model for retrospective identification of suspected infection for sepsis surveillance: a multicentre cohort study
Konstantin Föhse, Mihai Gheorghe Netea, Jaap ten Oever, Jacobien J. Hoogerwerf, Renée A M Tuinte, Hjalmar R. Bouma, Bram T. Knoop, Katrijn Van Deun, Tamar J. van der Aart, Luuk P J Smolenaers
article en
1 citations
Abstract
No abstract available for this paper.
Publication Tag
EClinicalMedicineVol. 87
Institutions
University Medical Center Groningen (NL), Goethe-Institute United Kingdom (GB), University of Bonn (DE), Radboud University Nijmegen (NL), University of Groningen (NL), Tilburg University (NL), Radboud University Medical Center (NL), Radboud Institute for Molecular Life Sciences (NL)
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Development and validation of an interpretable machine learning model for retrospective identification of suspected infection for sepsis surveillance: a multicentre cohort study — Konstantin Föhse, Mihai Gheorghe Netea, et al. · EClinicalMedicine (2025) | TGRS Research Map | TGRS