Deep Learning: A Taxonomy of Modern Weapon to Combat COVID-19 Pandemic

摘要: The COVID-19 pandemic, which originated in Wuhan, China in late 2019, has in only ten months greatly impacted many people’s life. In addition to the enormous health cost, the necessary lockdowns and governmentmandated suspension to prevent the spread of the virus had a huge economic impact. Therefore, it is natural to look for technological solutions to lessen COVID-19’s impact. Artificial Intelligent (AI) and Machine Learning (ML) have made significant improvements in many different applications. One of the advanced and robust technologies in ML is Deep Learning (DL), which can be employed as a tool to not only help prevent initial infections but also to detect and monitor its progress and side effects. Fast and accurate COVID-19 infection detection and treatment of suspected patients is essential to make better decisions, ensure treatment, and even save patients’ lives. This paper presents a taxonomy in the field of DL algorithms aiming to cover both the technical novelties and empirical results techniques for COVID-19. In this regard,(i) we demonstrate possible DL algorithms capable of combating against COVID-19,(ii) we propose a comprehensive up to date perspective of DL algorithms in social prevention and medical treatment, and (iii) we identify the challenges in combating COVID-19.