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. 2023 Apr 15;13:6147. doi: 10.1038/s41598-023-32332-x

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© The Author(s) 2023

Open Access This 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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(A) correlation analysis using ggcorpot package, R software v 4.2; (B) Heat map analysis used to demonstrate important features. (C) The confusion matrix was used to compare the different machine-learning algorithms, figure B&C was plotted using Python v3.7. (D) ROC curve analysis revealed biomarker potency of miR-29c alone and in combination with miR-93 using R 4.2.2's combioROC package.