Table 3.

The comparison among the state-of-the-art semi-supervised classifiers and DME grading methods on MESSIDOR dataset

Method	Accuracy	Sensitivity	Specificity	F1-score
Neural network	0.909 $\pm$ 0.010	0.830 $\pm$ 0.015	0.931 $\pm$ 0.011	0.820 $\pm$ 0.012
Self-training [14]	0.951 $\pm$ 0.015	0.894 $\pm$ 0.011	0.961 $\pm$ 0.014	0.891 $\pm$ 0.018
Co-training [15]	0.960 $\pm$ 0.009	0.890 $\pm$ 0.012	0.960 $\pm$ 0.009	0.879 $\pm$ 0.013
Lim et al. [3]	0.852	0.809	0.902	Not reported
Sreejini and Govindan [4]	0.945	0.91	0.98	Not reported
Akram et al. [2]	0.973	0.926	0.978	Not reported
Proposed	0.975 $\mathrm{\pm }$ 0.010	0.946 $\mathrm{\pm }$ 0.011	0.982 $\mathrm{\pm }$ 0.017	0.942 $\mathrm{\pm }$ 0.009