Table 2.

Performance metrics of the test procedure.

Regression models	n	MAE, y	r	Pvalue	R2-scr
Age: ABIDE-II 10-fold CV on test set	58	1.63 ± 0.28	0.76 ± 0.07	<0.001	0.54 ± 0.1
Age: ABIDE-II model on ADHD-200 full data	922	1.64	0.72	<0.001	0.50
Age: ADHD-200 10-fold CV on test set	92	1.43 ± 0.22	0.84 ± 0.04	<0.001	0.62 ± 0.08
Age: ADHD-200 model on ABIDE-II full data	580	1.57	0.75	<0.001	0.56
Classification models	n	Precision	Recall	F1-scr	AUC-ROC
Gender: ABIDE-II, 10-fold CV on test set	58	0.87 ± 0.06	0.80 ± 0.08	0.83 ± 0.04	0.82 ± 0.06
Gender: ABIDE-II model on ADHD-200 full data	922	0.76	0.80	0.78	0.79
Gender: ADHD-200, 10-fold CV on test set	92	0.84 ± 0.03	0.81 ± 0.06	0.83 ± 0.03	0.85 ± 0.04
Gender: ADHD-200 model on ABIDE-II full data	580	0.90	0.87	0.89	0.89
ASD: ABIDE-II, 10-fold CV on test set	58	0.46 ± 0.04	0.70 ± 0.18	0.55 ± 0.06	0.54 ± 0.06
ADHD: ADHD-200, 10-fold CV on test set	92	0.48 ± 0.07	0.55 ± 0.20	0.50 ± 0.11	0.61 ± 0.07

The performance indicators from 10-fold cross-validation are presented in their averaged values ± standard deviation. The chosen model for the cross-data set evaluation is the best-performing model of 10-fold cross-validation. For the column titles, r is the Pearson's correlation between predicted and target ages, n is the sample size, and R2-scr is the prediction R² (also known as cross-validation R² or q²). Values in bold are metrics of the best-performing trained models. ASD: autism spectrum disorder; ADHD: attention deficit hyperactivity disorder.