COVID-19 detection based on convolution neural networks from CT-scan images: a review

<span lang="EN-US">The COVID-19 outbreak has been affecting the health of people all around world. With number confirmed cases and deaths still rising daily, so main aim is to detect positive as soon provide them with necessary treatment. The utilization imaging data including chest x-rays computed tomography (CT) was proven that would be beneficial for quickly diagnosing COVID-19. Since Computerized Tomography provides a huge images, recognizing these visual traits difficult take enormous amounts time radiologists automated diagnosis technologies deep learning (DL) models are recently screening in CT scans. This review paper presents different researches which used approaches various convolutional neural networks (CNN) image classification tasks well, large training, like ResNet, VGG, AlexNet, LeNet, GoogleNet, others severity assessments using images. As result, analysis on images essential save medical personnel disease prevention.</span>