Table 2.

Performance comparison of existing architectures and varying strategies with the proposed approach on the combined dataset. (CA: classwise accuracy (%), BACC: Balanced Accuracy (%)).

Input	Class	Precision	Recall	F1 Score	Sensitivity	Specificity	CA	BACC
Existing Architectures
E417	H	0.85	0.78	0.81	0.77	0.87	77.81	80.89
	G	0.68	0.80	0.74	0.79	0.86	79.88
	DR	0.86	0.85	0.86	0.85	0.93	85.10
SNet20	H	0.85	0.68	0.75	0.67	0.89	67.84	80.34
	G	0.60	0.90	0.72	0.89	0.77	89.65
	DR	0.96	0.84	0.89	0.83	0.98	83.51
EyeNET48	H	0.67	0.45	0.54	0.45	0.75	45.33	53.33
	G	0.37	0.54	0.44	0.54	0.61	54.02
	DR	0.55	0.61	0.57	0.60	0.71	61.63
Concatenated Images	H	0.87	0.70	0.78	0.70	0.89	70.40	78.56
	G	0.58	0.84	0.68	0.84	0.77	83.90
	DR	0.92	0.81	0.86	0.81	0.96	81.40
Ablation Work
With OD	H	0.87	0.75	0.81	0.75	0.89	75.24	82.25
	G	0.71	0.81	0.76	0.81	0.87	81.03
	DR	0.84	0.91	0.87	0.90	0.91	90.95
With vessels	H	0.83	0.81	0.82	0.81	0.85	81.35	82.67
	G	0.75	0.79	0.77	0.78	0.90	78.73
	DR	0.88	0.88	0.88	0.87	0.94	87.76
Without feature selection	H	0.81	0.84	0.83	0.84	0.82	84.24	81.02
	G	0.75	0.78	0.77	0.78	0.90	78.1
	DR	0.90	0.81	0.85	0.80	0.96	80.85
Proposed Approach
Proposed* (, )	H	0.83	0.81	0.82	0.81	0.85	81.00	83.0
	G	0.75	0.81	0.78	0.81	0.89	81.00
	DR	0.90	0.87	0.89	0.87	0.96	87.00
Proposed* (: 0.87, : 0.782, : 1.0)	H	0.91	0.78	0.84	0.78	0.93	78.14	85.23
	G	0.69	0.91	0.79	0.91	0.85	91.38
	DR	0.92	0.86	0.89	0.86	0.96	86.17