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Machine learning models to predict and benchmark PICU length of stay with application to children with critical bronchiolitis.
Rogerson, Colin M; Heneghan, Julia A; Kohne, Joseph G; Goodman, Denise M; Slain, Katherine N; Cecil, Cara A; Kane, Jason M; Hall, Matt.
Afiliação
  • Rogerson CM; Division of Pediatric Critical Care, Indiana University School of Medicine, Indianapolis, Indiana, USA.
  • Heneghan JA; Division of Pediatric Critical Care, University of Minnesota Masonic Children's Hospital, Minneapolis, Minnesota, USA.
  • Kohne JG; Department of Pediatrics, Division of Critical Care Medicine, University of Michigan, Ann Arbor, Michigan, USA.
  • Goodman DM; Susan B. Meister Child Health Evaluation and Research Center, University of Michigan School of Medicine, Ann Arbor, Michigan, USA.
  • Slain KN; Northwestern University Feinberg School of Medicine and Ann & Robert H. Lurie Children's Hospital of Chicago, Division of Pediatric Critical Care Medicine, Chicago, Illinois, USA.
  • Cecil CA; Division of Pediatric Critical Care, University Hospitals Rainbow Babies & Children's Hospital, Cleveland, Ohio, USA.
  • Kane JM; Northwestern University Feinberg School of Medicine and Ann & Robert H. Lurie Children's Hospital of Chicago, Division of Pediatric Critical Care Medicine, Chicago, Illinois, USA.
  • Hall M; Department of Pediatrics, Section of Pediatric Critical Care Medicine, Comer Children's Hospital, University of Chicago, Chicago, Illinois, USA.
Pediatr Pulmonol ; 58(6): 1777-1783, 2023 06.
Article em En | MEDLINE | ID: mdl-37014153
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bronquiolite / Benchmarking Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Child / Child, preschool / Humans / Infant Idioma: En Ano de publicação: 2023 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: Bronquiolite / Benchmarking Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Child / Child, preschool / Humans / Infant Idioma: En Ano de publicação: 2023 Tipo de documento: Article