Comparative Analysis of Deep Learning Models for Covid-19 Detection from Chest X-rays

ABSTRACT

Lungs are the organs which play key role in human respiratory system. The severity of infections caused to the lungs might vary from mild to moderate. Chest X-Ray is a principal diagnostic tool used in detecting various types of lung diseases. The whole world is struggling due to a pandemic arised in 2019, known as Coronavirus disease or Covid-19, a severe respiratory infection. The medical industry demanded the use of computer aided techniques for analysing extremity of the disease. This work aims to examine the effectiveness of pretrained deep learning models in classifying chest X-rays as Covid, Viral pneumonia and Healthy cases. We have used largest publicly accessible Covid dataset, QaTa Cov-19 for conducting experiments. Out of six fine tuned deep learning pretrained network models, Densenet 201 outperformed with highest accuracy of 98.6% and AUC of 0.9996. © 2022 IEEE.