COVID-19 image classification techniques in medical analysis using deep representations

Abstract

Covid-19 is a fast-growing disease that affects human health with contacts nowadays. The medical community has not found any vaccine for immediate use, and some countries recently released vaccines. The human health and financial status of various countries spoiled recently with this virus. COVID-19 vaccine research is at the clinical trial stage in many countries. Mainly this disease affects the lungs of the patients. Recently deep learning approaches are widely using in radiographic image classifications with large-scale data. Convolutional Neural Networks (CNN) are widely used to diagnose COVID-19 pneumonia classification on Chest radiographic images to help radiologists in medical analysis. Recently some researchers developed tools to detect the virus, and they reduce the time of chest X-ray interpretation. This article discusses methods that can help protect themselves from those already infected with the virus by classifying the large-scale radiographic images with deep learning models. This study compares various methodologies and observes exciting insights for future research directions. © 2021 Author(s).