Table 6.

Performance achieved by different methods

Method	Dataset	PPV	Sensitivity	F-Score	Kappa score	AUROC	Accuracy
Proposed	He et al. [33]	0.904	0.917	0.91	0.8305	0.963	0.916
He et al. [13]	He et al. [33]	–	–	0.85	–	0.94	0.86
Sakagianni et al. [21]	He et al. [33]	0.8831	0.8831	–	–	–	–
Anwar and Zakir [3]	He et al. [33]	–	–	–	–	0.90	0.90
Wu et al. [27]	Private	–	0.811	–	–	0.819	0.76
Pu et al. [19]	Private	–	-	–	–	0.70	–
Xu et al. [28]	Private	0.813	0.867	0.839	–	–	0.867
Mei et al. [15]	Private	–	0.843	–	–	0.92	–
Polsinelli et al. [18]	He et al. [33]	0.8501	0.8755	0.8620	–	–	0.8503
Wang et al. [26]	Private	–	0.974	–	–	0.991	–
Di et al. [8]	Private	0.9065	0.9327	–	–	–	0.8979
Gao et al. [11]	Private	–	0.8914	–	–	0.9755	0.9599
Zhang et al. [32]	Private	–	0.9444	–	–	–	0.9403
Yener and Oktay [29]	Kaggle, He et al. [33]	0.90	0.94	0.92	–	0.91	0.91
Ouyang et al. [16]	Private	–	0.869	0.820	–	0.944	0.875

Performance attained by the proposed method (ensemble of CNNs+KSVM) is shown in bold