ABSTRACT
Given the infection's wide growth, one of the biggest challenges on the planet right now is identifying Corona Virus Disease 2019 (COVID-19). Recent findings show that, with over 225M confirmed instances, the number of people who have been diagnosed with COVID-19 is drastically increasing;Around the world, the sickness is affecting several countries. In this study, the global COVID-19 circulation incidence is briefly examined, and a deep convolutional neural network (CNN) artificial intelligence model is developed to identify COVID19 patients using real-world information. To find such patients, the model looks at chest CT scan images. The results show that such an approach is helpful in diagnosing COVID-19 since CT scans are easily accessible fast and inexpensively. This suggested approach is effective at detecting COVID-19 and achieves an F-measure range of 95-99%, according to empirical findings from 100 CT scan pictures of actual patients. The suggested model has a considerable impact in identifying sick individuals. © 2022 IEEE.