Using Transfer Learning for Automatic Detection of Covid-19 from Chest X-Ray Images

Abstract

The hasty spread of the perilous coronavirus has resulted in a significant loss of human life and unprecedented public health challenges around the world. Early screening of COVID-19 followed by an immediate medical response can halt the spread of the infection. The deep learning algorithms coupled with chest X-ray images provide fast and accurate results. This study aims to fine-tune seven pre-trained models for COVID-19 detection using chest X-ray radiographs. A sample of 3428 chest X-ray images comprising 1626 COVID-19 images was used to train and validate the models. The Inception V3 model outperformed the other models with an accuracy of 99.42%.