Development and validation of an interpretable machine learning model for retrospective identification of suspected infection for sepsis surveillance: a multicentre cohort study.
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| Title: | Development and validation of an interpretable machine learning model for retrospective identification of suspected infection for sepsis surveillance: a multicentre cohort study. |
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| Authors: | Tuinte RAM; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.; Radboud Community for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands., Smolenaers LPJ; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.; Radboud Community for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.; Tilburg School of Economics and Management, Tilburg University, the Netherlands.; AethiQs B.V., the Netherlands., Knoop BT; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.; Radboud Community for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands., Föhse K; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.; Radboud Community for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands., van der Aart TJ; Department of Acute Care, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.; Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands., Bouma HR; Department of Acute Care, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.; Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.; Department of Clinical Pharmacy & Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands., Netea MG; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.; Radboud Community for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.; Department of Immunology and Metabolism, Life and Medical Sciences Institute, University of Bonn, Bonn, Germany., Van Deun K; Department of Methodology & Statistics, Tilburg University, the Netherlands., Ten Oever J; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.; Radboud Community for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands., Hoogerwerf JJ; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.; Radboud Community for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands. |
| Source: | EClinicalMedicine [EClinicalMedicine] 2025 Aug 08; Vol. 87, pp. 103401. Date of Electronic Publication: 2025 Aug 08 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: The Lancet Country of Publication: England NLM ID: 101733727 Publication Model: eCollection Cited Medium: Internet ISSN: 2589-5370 (Electronic) Linking ISSN: 25895370 NLM ISO Abbreviation: EClinicalMedicine Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 40823498 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Development and validation of an interpretable machine learning model for retrospective identification of suspected infection for sepsis surveillance: a multicentre cohort study. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Tuinte+RAM%22">Tuinte RAM</searchLink>; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.; Radboud Community for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.<br /><searchLink fieldCode="AU" term="%22Smolenaers+LPJ%22">Smolenaers LPJ</searchLink>; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.; Radboud Community for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.; Tilburg School of Economics and Management, Tilburg University, the Netherlands.; AethiQs B.V., the Netherlands.<br /><searchLink fieldCode="AU" term="%22Knoop+BT%22">Knoop BT</searchLink>; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.; Radboud Community for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.<br /><searchLink fieldCode="AU" term="%22Föhse+K%22">Föhse K</searchLink>; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.; Radboud Community for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.<br /><searchLink fieldCode="AU" term="%22van+der+Aart+TJ%22">van der Aart TJ</searchLink>; Department of Acute Care, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.; Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.<br /><searchLink fieldCode="AU" term="%22Bouma+HR%22">Bouma HR</searchLink>; Department of Acute Care, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.; Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.; Department of Clinical Pharmacy & Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.<br /><searchLink fieldCode="AU" term="%22Netea+MG%22">Netea MG</searchLink>; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.; Radboud Community for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.; Department of Immunology and Metabolism, Life and Medical Sciences Institute, University of Bonn, Bonn, Germany.<br /><searchLink fieldCode="AU" term="%22Van+Deun+K%22">Van Deun K</searchLink>; Department of Methodology & Statistics, Tilburg University, the Netherlands.<br /><searchLink fieldCode="AU" term="%22Ten+Oever+J%22">Ten Oever J</searchLink>; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.; Radboud Community for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.<br /><searchLink fieldCode="AU" term="%22Hoogerwerf+JJ%22">Hoogerwerf JJ</searchLink>; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.; Radboud Community for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101733727%22">EClinicalMedicine</searchLink> [EClinicalMedicine] 2025 Aug 08; Vol. 87, pp. 103401. <i>Date of Electronic Publication: </i>2025 Aug 08 (<i>Print Publication: </i>2025). – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22The+Lancet%22">The Lancet </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101733727 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Internet <i>ISSN: </i>2589-5370 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2225895370%22">25895370 </searchLink><i>NLM ISO Abbreviation: </i>EClinicalMedicine <i>Subsets: </i>PubMed not MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=40823498 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.eclinm.2025.103401 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 103401 Titles: – TitleFull: Development and validation of an interpretable machine learning model for retrospective identification of suspected infection for sepsis surveillance: a multicentre cohort study. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Tuinte RAM – PersonEntity: Name: NameFull: Smolenaers LPJ – PersonEntity: Name: NameFull: Knoop BT – PersonEntity: Name: NameFull: Föhse K – PersonEntity: Name: NameFull: van der Aart TJ – PersonEntity: Name: NameFull: Bouma HR – PersonEntity: Name: NameFull: Netea MG – PersonEntity: Name: NameFull: Van Deun K – PersonEntity: Name: NameFull: Ten Oever J – PersonEntity: Name: NameFull: Hoogerwerf JJ IsPartOfRelationships: – BibEntity: Dates: – D: 08 M: 08 Text: 2025 Aug 08 Type: published Y: 2025 Identifiers: – Type: issn-electronic Value: 2589-5370 Numbering: – Type: volume Value: 87 Titles: – TitleFull: EClinicalMedicine Type: main |
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