COVID-19 Lungs Assessment in Chest X-ray Images using Convolutional Neural Networks

In the paper, the approach to classify COVID-19 in chest X-ray images is shown. The authors use 3175 Xray images: 540 cases of COVID-19 extracted from available datasets, 1294 viral pneumonia cases and 1339 cases taken from normal, healthy patients. 25 % of the images have been used as a training set. The classification results of COVID-19 using VGG19 and Xception networks resulted in >97.5% of the accuracy of COVID-19, >98.5%, of the balanced accuracy, around 97%, of the true -positive rate (sensitivity); ~1.0 F1 test and >0.97 Matthews correlation coefficient.