Machine Learning Algorithms Application in COVID-19 Disease: A Systematic Literature Review and Future Directions

Abstract

Since November 2019, the COVID-19 Pandemic produced by Severe Acute Respiratory Syndrome Severe Coronavirus 2 (hereafter COVID-19) has caused approximately seven million deaths globally. Several studies have been conducted using technological tools to prevent infection, to prevent spread, to detect, to vaccinate, and to treat patients with COVID-19. This work focuses on identifying and analyzing machine learning (ML) algorithms used for detection (prediction and diagnosis), monitoring (treatment, hospitalization), and control (vaccination, medical prescription) of COVID-19 and its variants. This study is based on PRISMA methodology and combined bibliometric analysis through VOSviewer with a sample of 925 articles between 2019 and 2022 derived in the prioritization of 32 papers for analysis. Finally, this paper discusses the study’s findings, which are directions for applying ML to address COVID-19 and its variants.

On the Implementation of the Artificial Neural Network Approach for Forecasting Different Healthcare Events

“…Machine learning (ML) is a branch of artificial intelligence that studies and develops ways for computers to learn on their own. ML has been successful in many areas, such as computer vision, detecting fraud, online advertising, automatic driving, and robotics [ 1 ]. The success of ML applications in fields, such as treatment, disease diagnosis, patient monitoring, epidemiology, and drug discovery, among others, makes it possible to predict the potential and influence of ML tools in designing and implementing new and better solutions in these areas [ 2 , 3 ].…”

“…The origin of the virus is still a matter of debate. According to genomic analyses [ 1 ], however, this virus is part of the bat- and rodent-hosting coronavirus family and is therefore classified as a member of the Beta-CoV (Corona Virus) genus group. Variants of the virus, including Delta and Omicron, have been responsible for various waves (high peaks) of infections and fatalities across the globe [ 6 ].…”