  The COVID-19 epidemic has become a major safety and health threat worldwide.
Imaging diagnosis is one of the most effective ways to screen COVID-19. This
project utilizes several open-source or public datasets to present an
open-source dataset of COVID-19 CXRs, named COVID-19-CXR-Dataset, and
introduces a deep convolutional neural network model. The model validates on
740 test images and achieves 87.3% accuracy, 89.67 % precision, and 84.46%
recall, and correctly classifies 98 out of 100 COVID-19 x-ray images in test
set with more than 81% prediction probability under the condition of 95%
confidence interval. This project may serve as a reference for other
researchers aiming to advance the development of deep learning applications in
medical imaging.
