AUTHOR=Barreto Tiago de Oliveira , Veras Nícolas Vinícius Rodrigues , Cardoso Pablo Holanda , Fernandes Felipe Ricardo dos Santos , Medeiros Luiz Paulo de Souza , Bezerra Maria Valéria , Andrade Filomena Marques Queiroz de , Pinheiro Chander de Oliveira , Sánchez-Gendriz Ignacio , Silva Gleyson José Pinheiro Caldeira , Rodrigues Leandro Farias , Morais Antonio Higor Freire de , dos Santos João Paulo Queiroz , Paiva Jailton Carlos , Andrade Ion Garcia Mascarenhas de , Valentim Ricardo Alexsandro de Medeiros 

TITLE=Artificial intelligence applied to analyzes during the pandemic: COVID-19 beds occupancy in the state of Rio Grande do Norte, Brazil

JOURNAL=Frontiers in Artificial Intelligence

VOLUME=Volume 6 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2023.1290022

DOI=10.3389/frai.2023.1290022

ISSN=2624-8212

ABSTRACT=The COVID-19 pandemic is already considered one of the biggest global health crises. In Rio Grande do Norte, a Brazilian state, the RegulaRN platform was the health information system used to regulate beds for patients with COVID-19. This article explored machine learning and deep learning techniques with RegulaRN data in order to identify the best models and parameters to predict the outcome of a hospitalized patient. A total of 25,366 bed regulations for COVID-19 patients were analyzed. The data analyzed comes from the RegulaRN Platform database from April 2020 to August 2022. From these data, the nine most pertinent characteristics were selected from the twenty available, and blank or inconclusive data were excluded.