A Survey on SARS-COV-2 (COVID-19) using Machine Learning Techniques

Abstract

SARS-CoV-2, widely known as (COVID-19), is a deadly contagious disease globally. The new suspicious virus is spreading quickly. Several studies have found that SARS and COVID-19 have comparable patterns of an inflammatory outbreak. The Coronavirus causes a severe respiratory disease that affects lung functions, and the transmission can occur through direct, close, or indirect contact from infected secretions or droplets. The typical symptom includes fever, persistent cough, cold, shortness of breath, pneumonia, decreased sense of smell, insomnia, brain fog, and many organ dysfunctions. Antibody tests and RT-PCR tests are used to diagnose fatal diseases. This literature review examines the occurrence and pathogenicity of COVID-19 infection along with radiological images, machine learning classifiers, feature extraction methods and disease prediction algorithms, and pattern recognition. This overview also summarizes the ML and DL algorithms and tools used for analysis.