Use of Artificial Intelligence to Standardize Imaging Exams of Patients with COVID-19

Abstract

Introduction: Covid -19 is a severe acute respiratory syndrome caused by the new coronavirus discovered in 2019 in Wuhan City, China, since then, this has been responsible for the contamination and death of millions across the globe. Objective: The aim of this review is to address the importance of the combination of natural and artificial intelligence associated with BIG DATA for the standardization of imaging tests of patients with COVID-19. Method: Literature review work based on research articles published nationally and internationally in databases, such as Scielo, PubMed, Lilacs, Radiology, Google Scholar and trusted government sites, in the period between 2004 and 2021. Development: Presentation of the etiological and clinical aspects of COVID-19, discussion of the main findings in computed tomography, use of Artificial Intelligence associated with BIG DATA in the context of the pandemic, in addition to the creation of the RadVid-19 program in Brazil. Conclusion: The incorporation of Artificial Intelligence associated with BIG DATA into medical practice proved to be efficient in diagnostic support, reduction in error rate, cross-cutting of clinical information and assistance in decision-making.
Descriptors: big data, COVID-19, artificial intelligence, data protection, RadVid-19, computed tomography