Multiclass Classification for Detection of COVID-19 Infection in Chest X-Rays Using CNN.

Alharbi, Rawan Saqer; Alsaadi, Hadeel Aysan; Manimurugan, S; Anitha, T; Dejene, Minilu

Alharbi, Rawan Saqer; Alsaadi, Hadeel Aysan; Manimurugan, S; Anitha, T; Dejene, Minilu.

Afiliación

Alharbi RS; Department of Artificial Intelligence, Industrial Innovation & Robotics Center, Faculty of Computers and Information Technology, University of Tabuk, Tabuk City, Saudi Arabia.
Alsaadi HA; Department of Artificial Intelligence, Industrial Innovation & Robotics Center, Faculty of Computers and Information Technology, University of Tabuk, Tabuk City, Saudi Arabia.
Manimurugan S; Department of Artificial Intelligence, Industrial Innovation & Robotics Center, Faculty of Computers and Information Technology, University of Tabuk, Tabuk City, Saudi Arabia.
Anitha T; Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (Deemed to be University), Chennai, Tamilnadu, India.
Dejene M; Department of Biotechnology, College of Biological and Chemical Engineering, Addis Ababa Science and Technology University, Addis Ababa, Ethiopia.

Comput Intell Neurosci ; 2022: 3289809, 2022.

Article en En | MEDLINE | ID: mdl-35965768

Asunto(s)

COVID-19; Aprendizaje Profundo; Neumonía; COVID-19/diagnóstico por imagen; Humanos; Redes Neurales de la Computación; Rayos X

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neumonía / Aprendizaje Profundo / COVID-19 Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: Comput Intell Neurosci Asunto de la revista: INFORMATICA MEDICA / NEUROLOGIA Año: 2022 Tipo del documento: Article País de afiliación: Arabia Saudita Pais de publicación: Estados Unidos

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