Application of Machine Learning to Infer Symptoms and Risk Factors of Covid-19

ABSTRACT

This article presents a model that aims to identify with Machine Learning (ML) technics the main symptoms and risk factors affected in patients with Coronavirus Covid-19, registered in the database of epidemiological surveillance of state and municipal information in Brazil. The concept behind ML is the ability to learn and reason. Its application can optimize and make the treatment and care process more accurate for the cases diagnosed with the Covid-19, also known as SARS-CoV-2, adjusting the medical data recorded concerning the disease and reducing the number of symptoms and risk factors, denoting an efficient form of attribute engineering, providing those involved with the clinical observation of a minor sign. We propose an approach structured in the composition of Machine Learning algorithms, aiming to discover knowledge and concepts followed by the refinement of the results. In this article, the proposed model is presented, and a shorter trail of symptomatic observations from Covid-19 are provided. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.