Review of COVID-19 Disease Prediction System Using CNN

Abstract

There has been an outbreak of Coronavirus Disease 2019 (COVID-19) since December 2019 across the globe. Imaging Modalities techniques like Real-time reverse transcription polymerase chain reaction imaging, CT scanning are very important for detection of COVID-19. Rapid reporting, cheap cost, and high sensitivity are all advantages of chest CT scan imaging in the diagnosis of lung infection. Deep-learning-based computer vision techniques, such as those used in X-rays, magnetic resonance imaging, and CT scan imaging, have recently shown tremendous potential. In order to build a deep-learning model, a large quantity of data is required, however medical staff are at risk of infection when collecting COVID-19 CT scan data since the illness is so contagious. Another problem is the scarcity of data labeling specialists. Our proposed adversarial conditional network is used to create realistic COVID-19 CT scan images for the use in deep learning-based diagnostic imaging tasks in order to synthesize CT scan images and to satisfy the data requirements for COVID-19 CT scan imaging. It will also be able to forecast how many patients will be admitted in the future days and how many will recover from the illness. We'll make use of the prophet program to make this prediction.