Table 3 Comparison in performance metrics of the DenseNet121-based classification model for each outcome class between the non-tilted vs. tilted disc images using the test dataset.
From: Deep learning-based optic disc classification is affected by optic-disc tilt
Outcome class | Metric | Non-tilted disc | Tilted disc | P-value |
---|---|---|---|---|
Normal | Accuracy | 0.962 ± 0.008 | 0.945 ± 0.009 | 0.05 |
Sensitivity | 0.967 ± 0.015 | 0.841 ± 0.032 | < 0.01 | |
Specificity | 0.958 ± 0.013 | 0.976 ± 0.009 | 0.15 | |
Precision | 0.940 ± 0.017 | 0.914 ± 0.028 | 0.23 | |
F1 score | 0.953 ± 0.009 | 0.876 ± 0.020 | < 0.01 | |
Glaucoma | Accuracy | 0.962 ± 0.009 | 0.939 ± 0.008 | 0.01 |
Sensitivity | 0.964 ± 0.013 | 0.965 ± 0.010 | 0.44 | |
Specificity | 0.955 ± 0.037 | 0.798 ± 0.044 | 0.02 | |
Precision | 0.988 ± 0.010 | 0.962 ± 0.008 | 0.03 | |
F1 score | 0.975 ± 0.006 | 0.964 ± 0.005 | 0.06 | |
Optic disc pallor | Accuracy | 0.960 ± 0.008 | 0.960 ± 0.009 | 0.43 |
Sensitivity | 0.981 ± 0.012 | 0.980 ± 0.010 | 0.44 | |
Specificity | 0.820 ± 0.058 | 0.608 ± 0.133 | 0.03 | |
Precision | 0.974 ± 0.008 | 0.978 ± 0.007 | 0.37 | |
F1 score | 0.977 ± 0.005 | 0.979 ± 0.005 | 0.40 | |
Optic disc swelling | Accuracy | 0.988 ± 0.005 | 0.985 ± 0.004 | 0.31 |
Sensitivity | 0.994 ± 0.005 | 0.999 ± 0.002 | 0.38 | |
Specificity | 0.899 ± 0.055 | 0.275 ± 0.189 | < 0.01 | |
Precision | 0.993 ± 0.004 | 0.986 ± 0.004 | 0.10 | |
F1 score | 0.994 ± 0.003 | 0.992 ± 0.002 | 0.31 |