Machine Learning Models to Detect COVID-19: An Overview

Severe pandemics like COVID-19 could cause persistent cough, muscular pains, sinus infections, and severe to serious respiratory diseases, according to a number of recent studies. The symptoms of such kind of illness show that COVID-19 has a harmful impact on the lungs. By applying CT scans and X-ray of the chest to assess the conditions of the lungs can considerably help in the diagnosis of COVID-19. So far, there are numerous techniques for identifying the coronavirus illness, but most of them take a very long time to check and may result in inaccurate outcomes. This research work aims to evaluate and administer image-based diagnosis procedures using artificial intelligence (AI) that have zero or near zero false-positive and false-negative rates. For this study, we will use artificial neural networks (ANN), ensemble learning (EL) and machine learning (ML) approaches in addition to the established AI image-based medical diagnosis procedures to develop a faster, real-time and efficient methodology for better detection and diagnosis of COVID-19.