A Survey of Machine Learning Technologies for COVID-19 Pandemic

Abstract

Intelligent technologies including machine learning and artificial intelligence are playing significant roles in human's battle against COVID-19 pandemic. Machine learning enables the machine to learn and improve on its own without being programmed in detail. Machine learning has now penetrated into many fields to help fight the epidemic. However, a specific and representative review of the contributions of machine learning is currently lacking. The purpose of this paper is to summarize several machine learning applications against COVID-19 including: i) predicting confirmed cases and trend, ii) classifying and diagnosing using ML-based images, and iii) managing medical resources. A database related to machine learning Technologies for COVID-19 is created. Moreover, a concise review is finished on the collected information by evaluating the different uses of machine learning against COVID-19. We also assemble researches in the present COVID-19 literature focused on ML-based methods in order to demonstrate a profound insight into COVID-19 related topics. Our discoveries emphasize crucial variables and available COVID-19 resources that facilitate clinical and translational research.