Table 4 ROC analysis presenting AUC values and the respective true positive (sensitivity) and true negative (specificity) rates for KID5 and iDA5 scores. The optimal cut-off point is achieved where the sensitivity and specificity values are close enough to the AUC value

From: Assessment of artificial intelligence model and manual morphokinetic annotation system as embryo grading methods for successful live birth prediction: a retrospective monocentric study