Detecting Covid-19 Induced Pneumonia from Chest X-ray Using CNNs

On the well-being and health of the global population, the COVID-19 pandemic continues to have a devastating impact. Health care systems around the world are facing challenges as a result of the rapid increase in patients with COVID-19. It is impossible to test every patient for the respiratory disease using conventional techniques (RT-PCR) due to the limited availability of testing kits. A crucial step in the fight against COVID-19 is the effective screening of infected patients, with radiologic imaging employing chest radiography being one of the main screening techniques. The purpose of this study was to automatically detect COVID-19 pneumonia patients using digital chest X-ray images while improving detection accuracy using convolutional neural networks (CNNs). The dataset includes COVID-19, viral pneumonia, and typical lung X-ray images. The CNN-based model has been proposed in this study to provide an accurate classification of coronavirus-pneumonia-infected patients using chest X-ray radiographs. The results demonstrate that CNNs are useful for classifying X-ray pictures as covid-free or influenced by covid. To raise accuracy to standards that can be used in medicine, more research and experimentation with professionals are required.