Fig. 4

Identification of minimal features for the best model performance and multiple metrics for model evaluation. A Average AUC of ten-fold Random Forest cross-validation, study-to-study transfer validation classifiers, and LOSO validation for non-irAEs versus irAEs with a different number of features. B Comparison of RF score distributions calculated by RF14 classifier between non-irAEs (n = 113) and irAEs (n = 77) groups. Two-sided P values were calculated using the Wilcoxon rank-sum test. C Performance measurements of RF14 classifier illustrated by sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV). D The comparison of microbiome model specificity between irAEs and response. The anti-PD1/PD-L1 cohorts comprising over 50 patients, such as those led by Zhang et al., Hakozaki et al., and McCulloch et al., were utilized for the analysis in this part