Abstract

The coronavirus (SARS-CoV-2), which causes severe acute respiratory syndrome (COVID-19), is the most current virus with the potential to kill a substantial number of people around the world. Current procedures are restrictive, time-consuming, inefficient, and obsolete. This is due to their exclusive reliance on the technical expertise of a radiologist or medical consultant. Deep learning and technological advancement have also enabled medical researchers and scientists to investigate various neural networks and algorithms to develop apps, tools, and gadgets that can assist medical radiologists. This paper aims to give an overview of deep learning techniques that have been used in chest radiography of COVID-19 and pneumonia cases, as well as the most important datasets that help researchers test algorithms.

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