Machine Learning, Deep Learning, and Mathematical Models to Analyze Forecasting and Epidemiology of COVID-19: A Systematic Literature Review.

Saleem, Farrukh; Al-Ghamdi, Abdullah Saad Al-Malaise; Alassafi, Madini O; AlGhamdi, Saad Abdulla

Saleem, Farrukh; Al-Ghamdi, Abdullah Saad Al-Malaise; Alassafi, Madini O; AlGhamdi, Saad Abdulla.

Afiliación

Saleem F; Department of Information System, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Al-Ghamdi ASA; Department of Information System, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Alassafi MO; Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
AlGhamdi SA; Ministry of Health, King Abdulaziz Hospital, Jeddah 22421, Saudi Arabia.

Int J Environ Res Public Health ; 19(9)2022 04 22.

Article en En | MEDLINE | ID: mdl-35564493

Asunto(s)

COVID-19; Aprendizaje Profundo; COVID-19/epidemiología; Predicción; Humanos; Aprendizaje Automático; Modelos Teóricos; SARS-CoV-2

Palabras clave

basic reproduction rate; deep learning; epidemiology of COVID-19; machine learning

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo / COVID-19 Tipo de estudio: Prognostic_studies / Qualitative_research / Screening_studies / Systematic_reviews Límite: Humans Idioma: En Revista: Int J Environ Res Public Health Año: 2022 Tipo del documento: Article País de afiliación: Arabia Saudita

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