Convolutional Neural Network Approach in Covid-19 Screening in Asymptomatic Individuals

Abstract

The new coronavirus (COVID-19) spread rapidly around the globe and hits around six million of cases as reported by the World Health Organization (WHO) at the time of writing. This growth in number of cases made it hard for doctors and radiologists to correctly diagnose the COVID-19 disease. The use of automated methods can be helpful to efficiently and accurately detect the disease, and can also be used to assist doctors who lack the proper tools for diagnosis. In the present study, we provide a novel method using Convolutional Neural Networks (CNN) to accurately classify COVID-19 cases from raw chest X-ray images by 95%. The proposed model is lightweight and can be easily deployed to the Cloud or mobile devices with little compute power.