Abstract

Timely and accurate screening/testing is crucial to fighting COVID-19. Compared to commonly used reverse transcriptase polymerase chain reaction (RT-PCR), chest radiography imaging (X-ray) is also a reliable, practical and rapid method to diagnose and assess COVID-19. In this paper, two types of deep learning models, namely, Convolutional Neural Networks (CNN) and Residual Neural Networks (ResNet) have been designed and tested for accurate diagnosis of COVID-19 with chest X-ray images. Experimental results demonstrate the effectiveness of the proposed approach.