Table 1.

Performance of Our Classification Model (Model 1) for Both Gradable and Ungradable Fundus Images in the Validation Dataset

Classification Metrics	Gradable (n = 13 717) Mean [95% CI]	Ungradable (n = 2328) Mean [95% CI]
AUROC	0.9656 [0.9614, 0.9697]	0.9656 [0.9613, 0.9699]
Accuracy	0.9713 [0.9688, 0.9738]	0.9712 [0.9687, 0.9738]
Sensitivity (recall)	0.9736 [0.9710, 0.9763]	0.9575 [0.9499, 0.9652]
Specificity	0.9574 [0.9491, 0.9657]	0.9736 [0.9709, 0.9763]
Precision	0.9926 [0.9912, 0.9941]	0.8605 [0.8471, 0.8738]
F1-score	0.9830 [0.9815, 0.9846]	0.9063 [0.8981, 0.9145]

AUROC = area under the receiver operating characteristic curve; CI = confidence interval; n = number of fundus images.