Table 2.

Performance of classifiers for different features (modalities) in machine learning

Features	Accuracy	Accuracy bal	Sensitivity	Specificity	p value uncorrected
Hybrid	87.04%	85.80%	86.42%	85.19%	.003
Simplified model	79.97	68.52	66.67	68.52	.059
GMV	67.28%	66.05%	48.15%	51.58%	.069
FA of white matter	69.14%	68.52%	66.05%	64.81%	.052
Static fALFF	53.09%	55.56%	48.77%	46.29%	.370
Static DC	50.00%	50.00%	50.00%	43.21%	.518
Dynamic fALFF	46.91	49.38%	43.83	45.06	.588
Dynamic DC	47.53	49.38%	43.83	45.06	.562

The feature(s) have been highlighted in bold font if it remains p < .05 after FWE correction