Individual Factors Associated With COVID-19 Infection: A Machine Learning Study.

Ramírez-Del Real, Tania; Martínez-García, Mireya; Márquez, Manlio F; López-Trejo, Laura; Gutiérrez-Esparza, Guadalupe; Hernández-Lemus, Enrique

Ramírez-Del Real, Tania; Martínez-García, Mireya; Márquez, Manlio F; López-Trejo, Laura; Gutiérrez-Esparza, Guadalupe; Hernández-Lemus, Enrique.

Afiliação

Ramírez-Del Real T; Cátedras Conacyt, National Council on Science and Technology, Mexico City, Mexico.
Martínez-García M; Center for Research in Geospatial Information Sciences, Mexico City, Mexico.
Márquez MF; Clinical Research Division, National Institute of Cardiology "Ignacio Chávez", Mexico City, Mexico.
López-Trejo L; Clinical Research Division, National Institute of Cardiology "Ignacio Chávez", Mexico City, Mexico.
Gutiérrez-Esparza G; Institute for Security and Social Services of State Workers, Mexico City, Mexico.
Hernández-Lemus E; Cátedras Conacyt, National Council on Science and Technology, Mexico City, Mexico.

Front Public Health ; 10: 912099, 2022.

Article em En | MEDLINE | ID: mdl-35844896

Assuntos

COVID-19; COVID-19/epidemiologia; Humanos; Aprendizado de Máquina; Redes Neurais de Computação; Pandemias; SARS-CoV-2

Palavras-chave

COVID-19; feature selection; imbalanced data; machine learning; predictive model

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Prognostic_studies / Risk_factors_studies Aspecto: Patient_preference Limite: Humans Idioma: En Revista: Front Public Health Ano de publicação: 2022 Tipo de documento: Article País de afiliação: México País de publicação: Suíça

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