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. 2023 Mar 7;14:1134325. doi: 10.3389/fendo.2023.1134325

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Copyright © 2023 Zhong, Zhu, Li, Gong, Xu, Zhong, Gong, Jiang, Wang, Fei, Tang, Lei, Wang and Zheng

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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Identification of diagnostic markers. (A, B) A least operator shrinkage and selection operator (LASSO) logistic regression was used to screen characteristic variables. (C) The relationship between the number and the error of random forest. Red, green, and blue represent the error of C1 subtype, C2 subtype and all samples. (D) Ordination plot of gene importance scores. (E) The accuracy curve of characteristic variables for the first 200 genes using the support vector machine–recursive feature eliminator (SVM–RFE) algorithm. The red circle indicates the position with the highest accuracy. (F) Venn diagram showing the intersection feature variables filtered by the three algorithms.