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

• DOI: 10.3390/electronics11234015
• Publication Date: 2022-12-05T09:40:09Z
• Authors: Dixon Salcedo; Cesar Guerrero; Khalid Saeed; Johan Mardini; Liliana Calderon-...; Carlos Henriquez; Andres Mendoza
• Keywords: Pandemic; 2019-20 coronavirus outbreak; Prioritization; Sample (material)

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