Performance evaluation of selected machine learning algorithms for COVID-19 prediction using routine clinical data: With versus Without CT scan features.

Shanbehzadeh, Mostafa; Kazemi-Arpanahi, Hadi; Orooji, Azam; Mobarak, Sara; Jelvay, Saeed

Shanbehzadeh, Mostafa; Kazemi-Arpanahi, Hadi; Orooji, Azam; Mobarak, Sara; Jelvay, Saeed.

Afiliación

Shanbehzadeh M; Assistant Professor of Health Information Management, Department of Health Information Technology, School of Paramedical, Ilam University of Medical Sciences, Ilam, Iran.
Kazemi-Arpanahi H; Assistant Professor of Health Information Management, Department of Health Information Technology, Abadan University of Medical Sciences, Abadan, Iran.
Orooji A; Assistant Professor of Health Information Management, Student Research Committee, Abadan University of Medical Sciences, Abadan, Iran.
Mobarak S; Assistant Professor of Medical Informatics, School of Medicine, North Khorasan University of Medical Science, North Khorasan, Iran.
Jelvay S; Assistant Professor of Infectious Diseases, School of Medicine, Abadan University of Medical Sciences, Abadan, Iran.

J Educ Health Promot ; 10: 285, 2021.

Article en En | MEDLINE | ID: mdl-34667785

Palabras clave

Artificial intelligence; COVID-19; computed tomography scan; coronavirus; data mining; machine learning; random forest

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Educ Health Promot Año: 2021 Tipo del documento: Article País de afiliación: Irán

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