Fig. 2

A model was built and validated by a machine learning-based approach. (A) The best model was identified using 113 different machine learning algorithms; (B–E) ROC curves of each dataset and training set, with the AUC values close to 1.0, indicating that the model has good discriminatory ability; (F) Volcano plot of the model genes; (G) Expression levels of the model genes in normal and tumor samples; (H) Correlation analysis between the model genes; (I) Model genes’ ROC curves, with ST14 gene showing the best performance; (J) Protein interaction network of model genes. *p < 0.05; **p < 0.01; ***p < 0.001.