Strategies for building robust prediction models using data unavailable at prediction time.

Yang, Haoyu; Tourani, Roshan; Zhu, Ying; Kumar, Vipin; Melton, Genevieve B; Steinbach, Michael; Simon, Gyorgy

Yang, Haoyu; Tourani, Roshan; Zhu, Ying; Kumar, Vipin; Melton, Genevieve B; Steinbach, Michael; Simon, Gyorgy.

Afiliação

Yang H; Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, USA.
Tourani R; Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA.
Zhu Y; Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA.
Kumar V; Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, USA.
Melton GB; Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA.
Steinbach M; Department of Surgery, University of Minnesota, Minneapolis, Minnesota, USA.
Simon G; Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, USA.

J Am Med Inform Assoc ; 29(1): 72-79, 2021 12 28.

Article em En | MEDLINE | ID: mdl-34963141

Assuntos

Infecção Hospitalar; Infecção Hospitalar/epidemiologia; Hospitais; Humanos; Modelos Logísticos; Morbidade

Palavras-chave

artificial intelligence; hospital-acquired infection; machine learning; predictive modeling

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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