Deep Learning Models for COVID-19 and Pneumonia Detection

In the recent years of development, deep learning (DL) is very useful in all fields with the growing availability of data. The main goal of DL technology is to make faster, reliable, and good decisions. Because of this ability, DL has found its use in healthcare, particularly with a focus on various types of medical images or images related to patients’ health. These fields have diagnostic processes that depend on gathering and processing large amounts of medical images. This work proposes a deep learning (DL) model based on “Convolutional Neural Network (CNN)” for identifying COVID-19 and Pneumonia using Chest X-Ray images. The result of this processing helps the radiologists to derive insights and make decisions to determine the correct diagnosis of the patient. This model helps in two ways. Firstly, to classify whether a chest X-ray shows any sort of variations with respect to COVID-19 and pneumonia or not. Secondly, to classify with the help of normal chest X-ray images. Experiments were carried out using InceptionV3 (IV3), and VGG16 models on the chest X-ray images. Results revealed that the VGG16 model outperformed IV3 model for COVID-19 and pneumonia identification on multiple performance metrics.