Table 1.

Model performance (AUROC, best sensitivity and specificity, PPV)

Model Type	Time split	AUROC (95%CI)	Specificity (balanced model)	Sensitivity (balanced model)	PPV (balanced model)	Sensitivity for 95% specificity	PPV at 95% specificity
Logistic Regression with Lasso	1, 2–5	0.736 (0.728–0.743)	0.752	0.602	0.156	0.222	0.254
Naïve Bayes Classifier	1, 2–5	0.682 (0.675–0.690)	0.906	0.241	0.164	0.153	0.189
Support Vector Machine	1, 2–5	0.737 (0.730–0.744)	0.691	0.674	0.142	0.223	0.255
Random Forest	1, 2–5	0.734 (0.726–0.740)	0.653	0.700	0.134	0.210	0.239
Neural Network (3 × 139 nodes)	1, 2–5	0.737 (0.730–0.743)	0.781	0.619	0.178	0.298	0.312