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. 2022 Apr 27;13:844283. doi: 10.3389/fmicb.2022.844283

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Copyright © 2022 Oliveira, Mwangi, Sartim, Delafiori, Sales, de Oliveira, Busanello, Val, Xavier, Costa, Baía-da-Silva, Sampaio, de Lacerda, Monteiro, Catharino and de Melo.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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An example of the prediction of SARS-CoV-2 infection severity according to the metabolomic profile of the plasma of the COVID-19 patients using the receiver operating characteristic (ROC) curve; (A) set of metabolites used for training; (B) ROC curve evidenced by the area under the curve (AUC) and CI 95%; (C) confusion matrix for calculating the proportion of false negatives, false positives, true negatives, and true positives; (D) performance metrics as sensitivity, specificity, accuracy, and precision. The figures were generated via MetaboAnalyst software v 4.0 (www.metaboanalyst.ca).