Fig. 3

Comparative analysis of the diagnostic accuracy in experiment 2, considering the best oscillometric parameter (BOP) obtained without the use of classifiers), machine learning algorithms, and the MIL classifier. K-NN K-Nearest Neighbor, ADAB Adaboost with decision tree classifiers, RF Random Forests, MIL Multiple Instance Learning, XGB Extreme Boosting Gradient Classifiers, AUC area under the ROC curve. Also, “*” indicates that there a statistically significant difference comparing to BOP (p < 0.05) and “**” (p < 0.01)