Table 2.

Performance of different machine learning models for predicting live birth outcome across three stages in test cohort.

Stage	Model	AUC (95% CI)	AUPRC (95% CI)	Brier Score	Accuracy	Sensitivity	Specificity	PPV	NPV	F1 score
1	Best Base	0.672 (0.643-0.702)	0.584 (0.543-0.628)	0.23	0.625	0.762	0.52	0.549	0.74	0.639
	SES	0.677 (0.649-0.707)	0.588 (0.547-0.633)	0.227	0.625	0.77	0.514	0.549	0.744	0.641
	Stacking	0.678 (0.649-0.708)	0.588 (0.547-0.633)	0.223	0.628	0.735	0.546	0.554	0.728	0.632
	DEP	0.674 (0.644-0.705)	0.591 (0.551-0.633)	0.227	0.619	0.79	0.487	0.542	0.751	0.643
2	Best Base	0.725 (0.698-0.751)	0.646 (0.604-0.690)	0.211	0.678	0.753	0.619	0.603	0.766	0.67
	SES	0.717 (0.687-0.742)	0.636 (0.595-0.679)	0.218	0.647	0.728	0.586	0.574	0.737	0.642
	Stacking	0.724 (0.695-0.749)	0.644 (0.603-0.689)	0.209	0.664	0.742	0.604	0.59	0.753	0.657
	DEP	0.697 (0.668-0.725)	0.611 (0.572-0.655)	0.222	0.647	0.697	0.61	0.578	0.723	0.632
3	Best Base	0.725 (0.698-0.753)	0.641 (0.601-0.686)	0.209	0.665	0.72	0.622	0.594	0.743	0.651
	SES	0.731 (0.704-0.757)	0.655 (0.616-0.700)	0.211	0.65	0.819	0.52	0.567	0.789	0.67
	Stacking	0.728 (0.701-0.755)	0.647 (0.608-0.691)	0.21	0.665	0.728	0.617	0.593	0.747	0.654
	DEP	0.721 (0.693-0.748)	0.653 (0.615-0.694)	0.214	0.666	0.616	0.704	0.615	0.705	0.616

Stage 1, baseline stage, the pre-IVF assessment period; Stage 2, stimulation stage, the ovarian stimulation phase; Stage 3, embryo development stage, embryological data including characteristics of embryos selected for transfer; AUC, area under the receiver operating characteristic curve; AUPRC, area under the precision-recall curve; PPV, positive predictive value; NPV, negative predictive value; SES, Static Ensemble Selection; DEP, Dynamic Ensemble Pruning; Best Base, best-performing base model.