Radiographic patterns on CT chest scans have shown higher sensitivity and specificity compared to RT-PCR detection of COVID-19 which, according to the WHO has a relatively low positive detection rate in the early stages. We technically review a study that compared multiple convolutional neural network (CNN) models to classify CT samples with COVID-19, Influenza viral pneumonia, or no-infection. We compare this mentioned study with one that is developed on existing 2D and 3D deep-learning models, combining them with the latest clinical understanding, and achieved an AUC of 0.996 (95%CI: 0.989–1.00) for Coronavirus vs Non-coronavirus cases per thoracic CT studies. They calculated a sensitivity of 98.2% and a specificity of 92.2%.
Deep learning system to screen coronavirus disease 2019 pneumonia