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.
CITATION STYLE
Victor, U., Dong, X., Li, X., Obiomon, P., & Qian, L. (2020). Effective COVID-19 Screening using Chest Radiography Images via Deep Learning. In 2020 4th International Conference on Multimedia Computing, Networking and Applications, MCNA 2020 (pp. 126–130). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/MCNA50957.2020.9264294
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