Sally M. Elghamrawy1, Aboul Ella Hassnien2,*, Vaclav Snasel3
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2353-2371, 2021, DOI:10.32604/cmc.2021.014767
Abstract Detecting COVID-19 cases as early as possible became a critical issue that must be addressed to avoid the pandemic’s additional spread and early provide the appropriate treatment to the affected patients. This study aimed to develop a COVID-19 diagnosis and prediction (AIMDP) model that could identify patients with COVID-19 and distinguish it from other viral pneumonia signs detected in chest computed tomography (CT) scans. The proposed system uses convolutional neural networks (CNNs) as a deep learning technology to process hundreds of CT chest scan images and speeds up COVID-19 case prediction to facilitate its containment. We employed the whale optimization… More >
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