Table 4.

Accuracies, sensitivities, specificities, and area under the curve (AUC) values of prediction models in an independent validation.

Machine learning algorithm	Accuracy	Sensitivity	Specificity	AUC
LR	0.746	0.756	0.727	0.755
SVM	0.746	0.844	0.545	0.731
SNN	0.716	0.867	0.409	0.707
RF	0.806	0.822	0.773	0.800
NB	0.776	0.822	0.682	0.743
Mean ± SD	0.758 ± 0.034	0.822 ± 0.042	0.627 ± 0.149	0.747 ± 0.034
95% CI	0.716–0.800	0.771–0.874	0.443–0.812	0.705–0.790

LR: logistic regression, SVM: support vector machine, SNN: standard neural network, RF: random forest, NB: naïve Bayes.