ABSTRACT
COVID-19 is one of the worst illnesses in history is a pandemic. The virus is known as SARS-COVID-2 because researchers have shown that it mostly affects the respiratory system and resembles the SARS variation. In some circumstances, it might cause pneumonia and a collapse of the respiratory system. To diagnose the patients' conditions and ascertain whether lung illness was involved, doctors used X-rays or Computed Tomography (CT) scans. In this study, pulmonary conditions associated with COVID-19 are identified and described using a deep learning method. To diagnose conditions including COV-19, lung cancer, and bacterial pneumonia, the suggested method makes use of CT scan pictures. A 2D picture from a CT scan offers more trustworthy results. The 50 layers of this method are organized into a ResNet-50 convolutional neural network (CNN). Comparing the experimental results to the current methods, a higher yield accuracy is predicted. © 2022 IEEE.