Maria Teresinha Arns Steiner1, David Gabriel de Barros Franco2, Pedro José Steiner Neto3
Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, Vol.38, No.3, pp. 1-15, 2022, DOI:10.23967/j.rimni.2022.09.001
- 09 September 2022
Abstract During the pandemic caused by the Coronavirus (Covid-19), Machine Learning (ML) techniques can be used, among other alternatives, to detect the virus in its early stages, which would aid a fast recovery and help to ease the pressure on healthcare systems. In this study, we present a Systematic Literature Review (SLR) and a Bibliometric Analysis of ML technique applications in the Covid-19 pandemic, from January 2020 to June 2021, identifying possible unexplored gaps. In the SLR, the 117 most cited papers published during the period were analyzed and divided into four categories: 22 articles that… More >
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