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. 2021 Jul 19;50(2):359–370. doi: 10.1007/s15010-021-01656-z

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© The Author(s) 2021

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 2 — Stability and performance of the minimalistic predictor. A Performance of the minimalistic predictor when leaving out one variable at a time (displayed on the x-axis). Leaving out a single variable from the identified binary variables did not markedly influence the performance. B Receiver operating characteristics (ROC) curve of the minimalistic predictor on the validation set considering only patients without any missing value (in the list of n = 20 variables for the minimalistic predictor). C ROC curve of SACOV-19 based on patients of the validation set without missing values (in the list of the 11 patient variables of SACOV-19)