Analysis of the construction and application effect of ophthalmic care service model based on telemedicine technology
oraz
19 mar 2025
O artykule
Data publikacji: 19 mar 2025
Otrzymano: 07 lis 2024
Przyjęty: 18 lut 2025
DOI: https://doi.org/10.2478/amns-2025-0523
Słowa kluczowe
© 2025 Ce Gao et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Performance comparison results of different models
| Model | Training accuracy/% | Verification accuracy/% | AUC/% | F1/% | Number of training parameters |
|---|---|---|---|---|---|
| ResNet50 | - | 91.93 | 74.32 | 88.24 | >8.6M |
| DenseNet121 | - | - | 79.35 | 89.32 | >27.80M |
| M2LC-Net | 98.10 | 92.46 | 84.24 | 86.13 | >29.35M |
| M2LC-Net without CAM | 99.16 | 94.86 | 88.35 | 87.35 | 2.97M |
Experimental results of different Dropout rates
| Discard rate | Accuracy/% | F1-score/% | Kappa/% | AUC/% |
|---|---|---|---|---|
| 0.1 | 75.48 | 91.54 | 71.08 | 96.38 |
| 0.2 | 78.53 | 92.43 | 73.28 | 97.93 |
| 0.3 | 74.25 | 93.24 | 74.18 | 98.24 |
| 0.4 | 76.35 | 92.93 | 74.01 | 97.24 |
| 0.5 | 78.24 | 94.32 | 75.23 | 93.99 |
| 0.6 | 77.24 | 94.03 | 74.26 | 94.72 |
| 0.7 | 76.35 | 95.36 | 71.24 | 92.46 |
| 0.8 | 76.32 | 94.11 | 74.29 | 94.24 |
| 0.9 | 70.36 | 90.24 | 68.92 | 92.53 |
Class-Wise performance of M2LC-Net mode
| Category | Accuracy rate | Precision rate | Sensitivity | Specificity |
|---|---|---|---|---|
| Normal | 0.58 | 0.61 | 0.48 | 0.69 |
| Diabetic retinopathy | 0.71 | 0.46 | 0.49 | 0.84 |
| Glaucoma | 0.88 | 0.25 | 0.21 | 0.93 |
| Cataract | 0.99 | 0.74 | 0.83 | 0.95 |
| Age-related macular degeneration | 0.97 | 0.61 | 0.21 | 0.95 |
| Hypertensive retinopathy | 0.94 | 0.18 | 0.07 | 0.91 |
| Nearsightedness | 0.98 | 0.73 | 0.94 | 0.99 |
| Other abnormal lesions | 0.81 | 0.38 | 0.37 | 0.87 |