Feature fusion based VGGFusionNet model to detect COVID-19 patients utilizing computed tomography scan images.

Uddin, Khandaker Mohammad Mohi; Dey, Samrat Kumar; Babu, Hafiz Md Hasan; Mostafiz, Rafid; Uddin, Shahadat; Shoombuatong, Watshara; Moni, Mohammad Ali

Uddin, Khandaker Mohammad Mohi; Dey, Samrat Kumar; Babu, Hafiz Md Hasan; Mostafiz, Rafid; Uddin, Shahadat; Shoombuatong, Watshara; Moni, Mohammad Ali.

Afiliación

Uddin KMM; Department of Computer Science and Engineering, Dhaka International University, Dhaka, 1205, Bangladesh.
Dey SK; School of Science and Technology, Bangladesh Open University, Gazipur, 1705, Bangladesh.
Babu HMH; Department of Computer Science and Engineering, University of Dhaka, Dhaka, 1000, Bangladesh.
Mostafiz R; Institute of Information Technology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh.
Uddin S; School of Project Management, Faculty of Engineering, The University of Sydney, Forest Lodge, NSW, 2037, Australia.
Shoombuatong W; Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700, Thailand. watshara.sho@mahidol.ac.th.
Moni MA; Artificial Intelligence and Digital Health Data Science, School of Health and Rehabilitation Sciences, Faculty of Health and Behavioural Sciences, The University of Queensland, St Lucia, QLD, 4072, Australia. m.moni@uq.edu.au.

Sci Rep ; 12(1): 21796, 2022 12 16.

Article en En | MEDLINE | ID: mdl-36526680

Asunto(s)

COVID-19; Humanos; COVID-19/diagnóstico por imagen; Brasil; Cintigrafía; Pacientes; Tomografía Computarizada por Rayos X

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Límite: Humans País/Región como asunto: America do sul / Brasil Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Bangladesh

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