Table 3.

The results of the classification network with different parameters

Classification network	G	R	Accuracy	Specificity	False positive	ROC (Area under curve)
ResNeSt14	1	2	0.733	0.852	8	0.689
	2	2	0.667	0.704	7	0.600
	1	4	0.733	0.741	5	0.659
ResNeSt18	1	2	0.756	0.852	7	0.711
	2	2	0.711	0.778	7	0.644
	1	4	0.733	0.889	9	0.687
ResNeSt50	1	2	0.756	0.852	7	0.703
	2	2	0.733	0.815	7	0.699
	1	4	0.711	0.815	8	0.653
ResNeSt101	1	2	0.756	0.815	6	0.689
	2	2	0.711	0.815	8	0.521
	1	4	0.711	0.704	5	0.660

ROC, receiver operating characteristic.