Deep learning based diagnosis of COVID-19 using chest CT-scan images

Abstract

The Coronavirus disease (COVID-19) is an infectious disease that primarily affects lungs. This virus has spread in almost every continent. Countries are racing to slow down the spread by testing and treating patients. To diagnose the infected people, reverse transcription-polymerase chain reaction (RT-PCR) test is used. Because of colossal demand; PCR kits are under shortage, and to overcome this; radiographic techniques such as X-rays and CT-scan can be used for diagnostic purpose. In this paper, deep learning technology is used to diagnose COVID-19 in subjects through chest CT-scan. EfficientNet deep learning architecture is used for timely and accurate detection of coronavirus with an accuracy 0.897, F1 score 0.896, and AUC 0.895. Three different learning rate strategies are used, such as reducing the learning rate when model performance stops increasing (reduce on plateau), cyclic learning rate, and constant learning rate. Reduce on plateau strategy achieved F1-score of 0.9, cyclic learning rate and constant learning rate resulted in F1score of 0.86 and 0.82, respectively.

Vision Transformer based COVID-19 Detection using Chest X-rays

“…Talha Anwar and others. [12] used the pretrained EfficientNet family of architectures to detect COVID-19 in CT scans and managed to get an accuracy score of 89.7%, an F1 score of 89.6%, and an AUC score of 89.5%.…”

Prognostication of Covid-19 and Heart Disease: A Combined Approach

“…Here, estimation is performed on which patients are likely to receive COVID-19 disease, using clinical prognosticative models with the help of deep learning and a Heart Disease Prediction system based on algorithms in machine learning. With accuracies of 85.5 for COVID-19 prediction and 80% for heart disease prediction, it could be highly effective in predicting COVID-19 [18] without much burden on existing methods like antigen test or RT-PCR test [20]. With widespread vaccination still being a distant scenario, fast prediction is the only possible option.…”

Detecting COVID-19 from chest computed tomography scans using AI-driven android application

“…It extracted features by using its learned weights on the ImageNet dataset [ 27 ]. T. Anwar et al used EfficientNet B4 to distinguish between COVID and normal CT-scan images with a 0.90 F1 score [ 28 ].…”