Artificial Intelligence and the Control of COVID-19: A Review of Machine and Deep Learning Approaches

Abstract

This study explores the prevalent Machine and Deep Learning approaches for the control of COVID-19. It reveals the impact of Artificial Intelligence in the case prediction, analysis, diagnosis, and treatment of the disease. Apart from discussing four (4) knowledge areas where Machine Learning and Deep Learning approaches were employed in the fight against the pandemic, we proposed a Generalized Artificial Intelligence Response Framework using those areas. We observed that most of the works seeking Artificial Intelligence scientific solutions to the pandemic were employing the use of chest X-ray images and chest computed tomography scans for prognosis and diagnosis while applying different Machine and Deep Learning approaches using available data dashboards. However, a production-ready landmark contribution towards the control of the disease through Artificial Intelligence is still at the moment a work in progress. Hence, the need for a response framework to give researchers and practitioners a working guide to finding solutions to the pandemic using computing techniques.