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. 2023 Jul 11;14:1205741. doi: 10.3389/fimmu.2023.1205741

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Copyright © 2023 Li, Long, Nong, Zheng, Meng and Zhu

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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Validation of a machine learning model based on 5 genes for predicting TB Validation of the 5-gene-based XGB model. (A) Construction of a nomogram for predicting the risk of TB clusters based on the 5-gene-based XGB model (C13orf18, PACS1, MGC18216, RNASE2, and PLAUR). (B) Construction of the calibration curve. Calibration curve analysis exhibited that solid line was near the dotted line,which suggesting the accuracy of the nomogram was relatively high. (C) Construction of the decision curve. DCA exhibited that the red line moved away from the gray line, which suggesting the accuracy of the nomogram was relatively high.