©The Author(s) 2026.
World J Radiol. Jan 28, 2026; 18(1): 115504
Published online Jan 28, 2026. doi: 10.4329/wjr.v18.i1.115504
Published online Jan 28, 2026. doi: 10.4329/wjr.v18.i1.115504
Table 3 Predictive performance of radiological models, clinical model and clinical-radiological model in prediction of hospital death on patients in the testing cohort
| Model | ROI | AUC (95%CI) | Accuracy | Sensitivity | Specificity | PPV | NPV | F1 score | Brier score |
| Xception | Hemorrhage | 0.517 (0.501-0.533) | 70.10 | 50.00 | 72.41 | 17.24 | 92.65 | 0.256 | 0.132 |
| Perihematomal edema | 0.513 (0.508-0.520) | 64.95 | 30.00 | 68.97 | 10.00 | 89.55 | 0.150 | 0.103 | |
| Combined | 0.549 (0.510-0.588) | 76.29 | 30.00 | 81.61 | 15.79 | 91.03 | 0.207 | 0.153 | |
| VGG16 | Hemorrhage | 0.580 (0.528-0.632) | 57.73 | 40.00 | 59.77 | 10.26 | 89.66 | 0.163 | 0.249 |
| Perihematomal edema | 0.584 (0.523-0.645) | 57.73 | 20.00 | 62.07 | 5.71 | 87.10 | 0.089 | 0.092 | |
| Combined | 0.607 (0.532-0.682) | 75.26 | 30.00 | 80.46 | 15.00 | 90.91 | 0.200 | 0.154 | |
| VGG19 | Hemorrhage | 0.586 (0.555-0.617) | 63.92 | 30.00 | 67.82 | 89.68 | 89.39 | 0.146 | 0.099 |
| Perihematomal edema | 0.606 (0.564-0.648) | 67.01 | 10.00 | 73.56 | 4.17 | 87.67 | 0.059 | 0.092 | |
| Combined | 0.654 (0.567-0.741) | 68.04 | 20.00 | 73.56 | 8.00 | 88.89 | 0.114 | 0.106 | |
| ResNet50 | Hemorrhage | 0.570 (0.510-0.630) | 67.01 | 40.00 | 70.11 | 13.33 | 91.04 | 0.200 | 0.173 |
| Perihematomal edema | 0.561 (0.512-0.610) | 71.13 | 50.00 | 73.56 | 17.86 | 92.75 | 0.263 | 0.149 | |
| Combined | 0.705 (0.606-0.804) | 64.95 | 60.00 | 65.52 | 16.67 | 93.44 | 0.261 | 0.254 | |
| InceptionV3 | Hemorrhage | 0.508 (0.500-0.517) | 72.16 | 40.00 | 75.86 | 16.00 | 91.67 | 0.229 | 0.309 |
| Perihematomal edema | 0.517 (0.509-0.525) | 62.89 | 40.00 | 65.52 | 11.76 | 90.48 | 0.182 | 0.120 | |
| Combined | 0.547 (0.516-0.578) | 68.04 | 50.00 | 70.11 | 16.13 | 92.42 | 0.244 | 0.142 | |
| InceptionResNetV2 | Hemorrhage | 0.502 (0.500-0.508) | 65.98 | 30.00 | 70.11 | 10.34 | 89.71 | 0.154 | 0.136 |
| Perihematomal edema | 0.597 (0.535-0.659) | 72.16 | 40.00 | 75.86 | 16.00 | 91.67 | 0.229 | 0.262 | |
| Combined | 0.615 (0.540-0.690) | 70.10 | 60.00 | 71.26 | 19.35 | 93.94 | 0.293 | 0.189 | |
| Handcrafted radiomics | Hemorrhage | 0.600 (0.546-0.654) | 70.10 | 60.00 | 71.26 | 19.35 | 93.94 | 0.293 | 0.223 |
| Perihematomal edema | 0.516 (0.505-0.527) | 57.73 | 30.00 | 60.92 | 8.11 | 88.33 | 0.128 | 0.127 | |
| Combined | 0.603 (0.534-0.672) | 67.01 | 50.00 | 68.97 | 15.63 | 92.31 | 0.238 | 0.168 | |
| Hematoma expansion | - | 0.546 (0.524-0.568) | 65.98 | 30.00 | 70.11 | 10.34 | 89.71 | 0.154 | 0.158 |
| Radiological model | - | 0.655 (0.576-0.734) | 67.01 | 30.00 | 71.26 | 10.71 | 89.86 | 0.158 | 0.208 |
| Integrated model | - | 0.754 (0.646-0.862) | 71.13 | 60.00 | 72.41 | 20.00 | 94.03 | 0.300 | 0.241 |
- Citation: Yang YH, Li Y. Deep learning-based imaging model to predict early hematoma enlargement and hospital mortality in spontaneous intracerebral hemorrhage. World J Radiol 2026; 18(1): 115504
- URL: https://www.wjgnet.com/1949-8470/full/v18/i1/115504.htm
- DOI: https://dx.doi.org/10.4329/wjr.v18.i1.115504