Deep-COVID: Predicting COVID-19 From Chest X-Ray Images Using Deep Transfer Learning

One of the crucial step in fighting COVID-19 is the ability to detect the infected patients early enough and put them under special care. Detecting this disease from radiography and radiology images is perhaps one of the fastest way to diagnose the patients. Some of the early studies showed specific abnormalities in the chest radiograms of patients infected with COVID-19.

Inspired by earlier works, this study applies deep learning models to detect COVID-19 patients from their chest radiography images. After preparing a dataset of 5,000 chest X-rays from the publicly available datasets, images exhibiting COVID-19 disease presence were identified by board-certified radiologist. Transfer learning on a subset of 2,000 radiograms was used to train four popular convolutional neural networks, including ResNet18, ResNet50, SqueezeNet, and DenseNet-121, to identify COVID-19 disease in the analyzed chest X-ray images. Read more in arXiv.

COVID-19 virus image via CDC