Machine learning approaches to predict the 1-year-after-initial-AMI survival of elderly patients.

Lee, Jisoo; Lee, Sulyun; Street, W Nick; Polgreen, Linnea A

Lee, Jisoo; Lee, Sulyun; Street, W Nick; Polgreen, Linnea A.

Afiliación

Lee J; Department of Business Analytics, University of Iowa, Iowa City, USA.
Lee S; Interdisciplinary Graduate Program in Informatics, University of Iowa, Iowa City, USA.
Street WN; Department of Business Analytics, University of Iowa, Iowa City, USA.
Polgreen LA; Department of Pharmacy Practice and Science, University of Iowa, Iowa City, USA. linnea-polgreen@uiowa.edu.

BMC Med Inform Decis Mak ; 22(1): 115, 2022 04 29.

Article en En | MEDLINE | ID: mdl-35488291

Asunto(s)

Infarto del Miocardio; Anciano; Antagonistas de Receptores de Angiotensina/uso terapéutico; Inhibidores de la Enzima Convertidora de Angiotensina/uso terapéutico; Angiotensinas/uso terapéutico; Femenino; Humanos; Aprendizaje Automático; Masculino

Palabras clave

Acute myocardial infarction (AMI heart attack); Hyper-parameter optimization; Lasso logistic regression (LLR); Machine learning; Nested cross-validation (CV); Random forest (RF); Sampling methods

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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Infarto del Miocardio Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Aged / Female / Humans / Male Idioma: En Revista: BMC Med Inform Decis Mak Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

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