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Integrating machine learning predictions for perioperative risk management: Towards an empirical design of a flexible-standardized risk assessment tool.
Abraham, Joanna; Bartek, Brian; Meng, Alicia; Ryan King, Christopher; Xue, Bing; Lu, Chenyang; Avidan, Michael S.
Afiliação
  • Abraham J; Institute for Informatics, School of Medicine, Washington University in St Louis, MO, United States; Department of Anesthesiology, School of Medicine, Washington University in St Louis, MO, United States. Electronic address: joannaa@wustl.edu.
  • Bartek B; Institute for Informatics, School of Medicine, Washington University in St Louis, MO, United States.
  • Meng A; Department of Anesthesiology, School of Medicine, Washington University in St Louis, MO, United States.
  • Ryan King C; Department of Anesthesiology, School of Medicine, Washington University in St Louis, MO, United States.
  • Xue B; Department of Electrical & Systems Engineering, McKelvey School of Engineering, Washington University in St Louis, MO, United States.
  • Lu C; Department of Computer Science & Engineering, McKelvey School of Engineering, Washington University in St Louis, MO, United States.
  • Avidan MS; Department of Anesthesiology, School of Medicine, Washington University in St Louis, MO, United States.
J Biomed Inform ; 137: 104270, 2023 01.
Article em En | MEDLINE | ID: mdl-36516944
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Cuidados Críticos / Cirurgiões Tipo de estudo: Etiology_studies / Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
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XML
PubMed Links
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Cuidados Críticos / Cirurgiões Tipo de estudo: Etiology_studies / Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article