Research Article
[Retracted] Automatic Detection of High-Frequency Oscillations Based on an End-to-End Bi-Branch Neural Network and Clinical Cross-Validation
Table 8
Classification performance with different structures.
| Group | Model | Confusion matrix | Evaluation metrics (%) | TN | FP | FN | TP | SEN | SPE | PRE | ACC | FDR | F1 |
| 1 | Bi- | 838 | 132 | 50 | 675 | 93.10 | 86.39 | 83.64 | 89.26 | 16.36 | 88.12 | TF- | 866 | 104 | 254 | 471 | 64.97 | 89.28 | 81.91 | 78.88 | 18.09 | 72.46 | Sig- | 768 | 202 | 69 | 656 | 90.48 | 79.18 | 76.46 | 84.01 | 23.54 | 82.88 |
| 2 | Bi- | 954 | 109 | 120 | 780 | 86.67 | 89.75 | 87.74 | 88.33 | 12.26 | 87.20 | TF- | 980 | 83 | 429 | 471 | 52.33 | 92.19 | 85.02 | 73.92 | 14.98 | 64.79 | Sig- | 886 | 177 | 92 | 808 | 89.78 | 83.35 | 82.03 | 86.30 | 17.97 | 85.73 |
| 3 | Bi- | 865 | 256 | 30 | 783 | 96.31 | 77.16 | 75.36 | 85.21 | 24.64 | 84.56 | TF- | 974 | 147 | 243 | 570 | 70.11 | 86.89 | 79.50 | 79.83 | 20.50 | 74.51 | Sig- | 815 | 306 | 22 | 791 | 97.29 | 72.70 | 72.11 | 83.04 | 27.89 | 82.83 |
| 4 | Bi- | 2282 | 61 | 41 | 2370 | 98.30 | 97.40 | 97.49 | 97.85 | 2.51 | 97.89 | TF- | 2308 | 35 | 363 | 2048 | 84.94 | 98.51 | 98.32 | 91.63 | 1.68 | 91.14 | Sig- | 2098 | 245 | 18 | 2393 | 99.25 | 89.54 | 90.71 | 94.47 | 9.29 | 94.79 |
| 5 | Bi- | 2642 | 274 | 418 | 2487 | 85.61 | 90.60 | 90.08 | 88.11 | 9.92 | 87.79 | TF- | 2656 | 260 | 793 | 2112 | 72.70 | 91.08 | 89.04 | 81.91 | 10.96 | 80.05 | Sig- | 2288 | 628 | 174 | 2731 | 94.01 | 78.46 | 81.30 | 86.22 | 18.70 | 87.20 |
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