Table 2.

Performance of the binary and multiclass classifications and predictions by machine learning.

Binary Classification	K =	Sensitivity (Mean)	Sensitivity (SD)	Specificity (Mean)	Specificity (SD)	Accuracy (Mean)	Accuracy (SD)	AUC
stage I	5	1.0000	0.0000	1.0000	0.0000	1.0000	0.0000	1.0000
	3	0.9851	0.0313	1.0000	0.0000	0.9964	0.0073	0.9911
	2	0.9933	0.0210	1.0000	0.0000	0.9988	0.0037	0.9969
stage II	5	0.9334	0.0839	1.0000	0.0000	0.9857	0.0150	0.9702
	3	0.9607	0.0422	1.0000	0.0000	0.9913	0.0090	0.9803
	2	0.9711	0.0249	1.0000	0.0000	0.9931	0.0059	0.9852
stage III	5	1.0000	0.0000	1.0000	0.0000	1.0000	0.0000	1.0000
	3	1.0000	0.0000	0.9977	0.0071	0.9996	0.0011	0.9988
	2	0.9997	0.0009	0.9917	0.0148	0.9983	0.0025	0.9955
stage IV	5	1.0000	0.0000	1.0000	0.0000	1.0000	0.0000	1.0000
	3	0.9958	0.0087	0.9976	0.0073	0.9966	0.0054	0.9966
	2	0.9938	0.0103	0.9969	0.0097	0.9954	0.0063	0.9954
Multiclass classification	5	0.9244	0.0227	1.0000	0.0000	0.9338	0.0195	0.9881

AUC, area under the curve; SD, standard deviation.