A Comparative Study of SARS COVID-19 Using X-ray and CT Scan Images Using Deep Learning Techniques

Coronavirus disease (Covid-19) first came to light in 2019. It has spread across the world, which has led to a very strong ephemeral. As a result of its infection rate and severity, it has emerged as one of the significant ultimatums of the present generation. Since then, many academics and clinicians have worked on artificial intelligence-based models to predict Covid-19. It is easier to assess and cure the disease if it is detected and expected in an early stage. Moreover, using deep learning model techniques can decrease the time spent on traditional practices. As a result, our study stresses the use of deep learning patterns for interpreting medical images in Covid-19 patients. In addition, a comparison of numerous strategies for developing a deep learning model has been carried out. The goal is to create a deep learning architecture and compare and analyze performance metrics like accuracy, recall, precision, and F-score for deep learning methods used to detect SARS Covid-19 in an automated manner