A Review of an Effective Deep Learning Network for Estimating COVID-19 severity from chest X-ray Imagery: Co Severity-Net

Abstract

The COVID-19 pandemic has become an integral part of our existence and shows no signs of abating. In 2020, the World Health Organization declared it a pandemic, and its effects have impacted our lives in myriad ways. To detect COVID-19 from Chest X-Ray images, researchers have developed deep learning techniques. Given the severity of the disease, scoring the level of COVID-19 infection can aid in determining the optimal course of treatment and care for patients, as not all COVID-19 positive patients require specialized medical attention. However, the limited availability of a large-scale dataset has resulted in few studies being conducted to estimate the severity of the disease from Chest X-Ray images. Consequently, we propose CoV Severity-Net, a deep learning-based architecture trained on a public COVID-19 dataset curated by experienced radiologists for severity estimation. Our proposal is based on a review of 18 papers from reputable sources such as Google Scholar, PubMed, and Science Direct.