Coronavirus Disease (COVID-19) Detection using Deep Features Learning

Abstract Coronavirus (COVID-19) pandemic detection considers a critical and challenging task for the doctors. The coronavirus disease spread so rapidly between people and infected roughly fourteen million people worldwide. For this reason, it is very much necessary to detect infected people with coronavirus and take the action to prevent of spread this virus. In this study, the COVID-19 classification methodology is adopted to detect the infected patient with coronavirus using CT images. The deep learning is applied to recognize the affected CT images of COVID-19 from others by employing the deep feature. This methodology can be beneficial for the medical practitioner to diagnosis the infected patient with coronavirus. The result is based on new data collections named BasrahDataset that included different CT scan video for Iraqi patients. The system gives promised results with 99% F1-score for detecting COVID-19.