Table 2.

Performance of models on the training set (cross-validation).

Models	PRE	SEN	SPE	ACC	F1	ROC-AUC	PR-AUC
LR	0.7000	0.7831	0.5194	0.6747	0.7392	0.6764	0.7159
SVM	0.6909	0.9017	0.4223	0.7046	0.7824	0.7962	0.8553
Adaboost	0.7514	0.8915	0.5777	0.7625	0.8155	0.8245	0.8543
XGBoost	0.8054	0.8136	0.7184	0.7745	0.8094	0.8317	0.8748
LightGBM	0.7871	0.9525	0.6311	0.8204	0.8620	0.9225	0.9313
AutoML	0.8529	0.9627	0.7621	0.8802	0.9045	0.9537	0.9522