Research Article
[Retracted] Deep Learning-Based Diagnosis Method of Emergency Colorectal Pathology
Table 1
Diagnosis results of different methods in datasets D1 and D2.
| Data set | Method | TPR (%) | FPR (%) | TNR (%) | FNR (%) | ACC (%) |
| D1 | CIFAR1 | 89.19 | 10.81 | 90.7 | 9.3 | 90 | VGG1 | 91.89 | 8.11 | 93.02 | 6.98 | 92.5 |
| D2 | CIFAR2 | 89.19 | 10.81 | 100 | 0 | 94 | VGG2 | 94.6 | 5.4 | 97.67 | 2.33 | 96.25 |
| Warwick -QU | SegNet | 54.5 | 45.5 | 100 | 0 | 73.7 | Object-Net | 97.29 | 2.71 | 97.67 | 2.33 | 97.5 |
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