Table 2.

The classification evaluation results of various methods in both binary classification and multi-class classification scenarios

		Acc (%)	Pre (%)	Sp (%)	Se (%)	F1-score (%)	ROC AUC	PR AUC	MCC
Binary Classification Result
Internal	Wang et al. [37]	82.91	79.65	78.33	87.72	83.33	0.8714	0.8624	0.6623
	Lin et al. [38]	86.51	86.89	87.50	85.48	86.18	0.8950	0.9072	0.7301
	Zhou et al. [39]	82.54	81.25	81.25	83.87	82.54	0.8443	0.8486	0.6512
	proposed	95.24	96.67	96.87	93.55	95.08	0.9591	0.9636	0.9051
External	Wang et al. [37]	79.25	75.00	80.00	78.26	76.60	0.8216	0.8144	0.5801
	Lin et al. [38]	84.91	80.00	83.33	86.96	83.33	0.8765	0.8672	0.6979
	Zhou et al. [39]	77.36	70.37	73.33	82.61	76.00	0.8354	0.7953	0.5546
	proposed	92.45	88.00	90.00	95.65	91.67	0.9348	0.9215	0.8504
Multi-class Classification Result
Internal	Wang et al. [37]	82.40	81.11	91.36	82.12	81.51	0.8108	0.8076	0.7363
	Lin et al. [38]	85.33	84.45	92.73	85.07	84.72	0.8486	0.8642	0.7793
	Zhou et al. [39]	85.78	83.94	92.47	84.41	84.17	0.8675	0.8869	0.7785
	proposed	92.44	92.20	96.15	92.16	92.18	0.9190	0.9326	0.8845
External	Wang et al. [37]	79.45	79.36	89.61	79.98	79.61	0.8403	0.8243	0.7055
	Lin et al. [38]	82.19	81.93	91.09	82.75	82.16	0.8709	0.8688	0.7398
	Zhou et al. [39]	83.56	83.53	91.68	84.20	83.80	0.8921	0.8837	0.7669
	proposed	90.41	90.46	95.08	90.65	90.52	0.9134	0.9346	0.8631