Table 3.
Data characteristics of the internal (SMC) and external (Intermountain) dataset.
| Overall | Train | Validation | Test | External test (intermountain) |
|
|---|---|---|---|---|---|
| Number of studies | 1797 | 1461 | 167 | 169 | 200 |
| Median age (IQR) | 66.14 (53.24–82.40) | 66.13 (53.14–82.95) | 64.10 (50.88–78.38) | 67.24 (56.62–82.76) | 55.3 (42.0–69.5) |
| Number of patients (Female %) | 1773 (57.07%) | 1414 (56.64%) | 162 (67.36%) | 163 (52.08%) | 198 (58.5%) |
| Median number of slices (IQR) | 386 (134) | 385 (136) | 388 (132) | 388 (139) | 324 |
| Number of positive PE | 655 | 488 | 82 | 85 | 94 |
| Number of negative PE | 1142 | 973 | 85 | 84 | 106 |
The internal SMC dataset was divided into training, validation and test. The training set was used to optimize model parameters and the validation set was used to select the best model and operating points. The hold-out test set was used to evaluate the model’s performance. The external Intermountain dataset was used solely for evaluation.