Predicting COVID-19 and other Lung Related Diseases like Pneumonia and Tuberculosis using Deep Learning

Abstract

severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) provisionally named COVID-19 is a significant public health and wellness issue. It is rapidly dispersed around the world, leading to a colossal mortality rate. Pneumonia or lung infection is the most usual complication of COVID-19. The best and critical advance in battling COVID-19 is the capacity to recognize the tainted patients quickly and put them under seclusion. As a typical symptomatic apparatus, an X-Ray is fast and simple to secure absent a lot of costs. Developing a touchy analytic apparatus utilizing X-Ray pictures can accelerate the symptomatic cycle and is supplementing and steady to RT-PCR just as the Antigen-based tests. By benefiting the solid component learning capacity, profound learning techniques can mine highlights that are consequently relied upon to have quick and vigorous outcomes that are identified with clinical results from Chest X-Ray pictures. Subsequently, the point is to foster a profound learning framework to effectively recognize, characterize and distinguish amid COVID-19, viral Pneumonia and Tuberculosis from a bunch of chest X-Ray pictures utilizing profound learning techniques which could help exceptionally obliged clinical experts, professionals and analysts in deciding the route of medicine.