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Sepsis labels defined by claims-based methods are ill-suited for training machine learning algorithms.
de Hond, Titus A P; Niemantsverdriet, Michael S A; van Solinge, Wouter W; Oosterheert, Jan Jelrik; Haitjema, Saskia; Kaasjager, Karin A H.
Afiliação
  • de Hond TAP; Department of Internal Medicine and Acute Medicine, University Medical Center Utrecht, Universiteit Utrecht, Utrecht, the Netherlands. Electronic address: t.a.p.dehond@umcutrecht.nl.
  • Niemantsverdriet MSA; Central Diagnostic Laboratory, University Medical Centre Utrecht, Universiteit Utrecht, Utrecht, the Netherlands; SkylineDx, Rotterdam, the Netherlands.
  • van Solinge WW; Central Diagnostic Laboratory, University Medical Centre Utrecht, Universiteit Utrecht, Utrecht, the Netherlands.
  • Oosterheert JJ; Department of Internal Medicine and Infectious Diseases, University Medical Center Utrecht, Universiteit Utrecht, Utrecht, the Netherlands.
  • Haitjema S; Central Diagnostic Laboratory, University Medical Centre Utrecht, Universiteit Utrecht, Utrecht, the Netherlands.
  • Kaasjager KAH; Department of Internal Medicine and Acute Medicine, University Medical Center Utrecht, Universiteit Utrecht, Utrecht, the Netherlands.
Clin Microbiol Infect ; 28(8): 1170-1171, 2022 08.
Article em En | MEDLINE | ID: mdl-35364274
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sepse / Aprendizado de Máquina Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Clin Microbiol Infect Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sepse / Aprendizado de Máquina Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Clin Microbiol Infect Ano de publicação: 2022 Tipo de documento: Article