Table 6.

Diagnostic performance of HFBN versus traditional deep learning models (in %).

Deep Learning Models	ACC	SPE	SEN	AUC
ST-GCN	74.53	69.59	78.46	74.03
Kernel_trans	69.23	67.13	70.75	63.94
Brainnet_CNN	78.45	80.47	76.02	78.25
HFBN	82.34	82.09	80.41	81.25

Note: ACC=accuracy (in %); SPE=specificity (in %); SEN=sensitivity (in %); AUC=area under ROC curve; ROC=Receiver Operating Characteristic