Covid-19 Prediction Through Chest X-Ray Image Datasets Using Deep Learning

The work aims at the prediction and analysis of COVID-19 from Chest X-Ray scan images using Pre-trained Deep Convolutional Neural Network models. Analysis is carried out using two open-source datasets, to identify and differentiate between the Chest X-Ray scans of non COVID person and COVID-19 affected person. A baseline model using LeNet-5 is implemented using the initial dataset collected, which gave 98.57 % accuracy. Further, pre-trained models such as AlexNet, ResNet 50, Inception V3, VGG16, VGG19 and Xception are used for COVID prediction and carryout comparative analysis. Using the performance measures viz. Accuracy, Confusion Matrix and ROC Curves, the result of study shows that for the first dataset used for analysis, Xception and for the second dataset Inception architectures respectively are most suitable for the prediction of COVID-19.