Detecting COVID-19 and Pneumonia using CNN-GRU Model

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Abstract

This Research paper uses Gated Recurrent Units and Convolution Neural Networks to compare the X Ray images of the chest to classify COVID-19 and pneumonia, patients. This CNN-GRU model discussed in this paper is trained using a dataset that has images of chest X Rays of COVID-19 and Pneumonia patients. The above-mentioned model is also compared with related works in the same scope. This model is compared with ConvNet, AlexNet, and VGG-19 models. It can be seen that the combination of CNN and GRU can significantly improve the accuracy by achieving classification accuracy as high as 98.9%. This paper can also be useful to develop machine-learning models for classifying and diagnosing respiratory diseases.

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Keywords

Pneumonia; COVID-19; CNN; GRU; VGG19 models; X-ray