Deep Learning Based Early Detection Framework for Preliminary Diagnosis of COVID-19 via Onboard Smartphone Sensors.

Khaloufi, Hayat; Abouelmehdi, Karim; Beni-Hssane, Abderrahim; Rustam, Furqan; Jurcut, Anca Delia; Lee, Ernesto; Ashraf, Imran

Khaloufi, Hayat; Abouelmehdi, Karim; Beni-Hssane, Abderrahim; Rustam, Furqan; Jurcut, Anca Delia; Lee, Ernesto; Ashraf, Imran.

Afiliação

Khaloufi H; LAROSERI Laboratory, Department of Computer Science, Faculty of Sciences, Chouaib Doukali University, El Jadida 24000, Morocco.
Abouelmehdi K; LAROSERI Laboratory, Department of Computer Science, Faculty of Sciences, Chouaib Doukali University, El Jadida 24000, Morocco.
Beni-Hssane A; LAROSERI Laboratory, Department of Computer Science, Faculty of Sciences, Chouaib Doukali University, El Jadida 24000, Morocco.
Rustam F; Department of Computer Science, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan 64200, Pakistan.
Jurcut AD; School of Computer Science, University College Dublin, Belfield, Dublin 4, Ireland.
Lee E; Department of Computer Science, Broward College, Broward County, FL 33332, USA.
Ashraf I; Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Korea.

Sensors (Basel) ; 21(20)2021 Oct 15.

Article em En | MEDLINE | ID: mdl-34696066

Assuntos

COVID-19; Aprendizado Profundo; Inteligência Artificial; Humanos; Pandemias; SARS-CoV-2; Smartphone

Palavras-chave

COVID-19 prediction; deep learning; prediction framework; smartphone sensors

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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Aprendizado Profundo / COVID-19 Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Marrocos

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