Table 4.
Comparison of model performance based on sensitivity, specificity, and false alert rate with different characterizations of hypoglycemic events and different validation strategies (patient-based and time-based) for giving predictive alerts.
| Model | 30-minute prediction horizon | 60-minute prediction horizon | |||||
|
|
Sensitivity (%) | Specificity (%) | False alert rate (%) | Sensitivity (%) | Specificity (%) | False alert rate (%) | |
| All hypoglycemic events prediction (5-fold validation) | 93.61 | 93.50 | 84.94 | 91.01 | 89.82 | 77.20 | |
| All hypoglycemic events prediction (new time periods) | 87.10 | 92.66 | 85.16 | 73.87 | 87.29 | 79.81 | |
| All hypoglycemic events prediction (new patients) | 87.60 | 92.47 | 75.20 | 73.79 | 87.06 | 71.50 | |
| Sustained hypoglycemic events prediction (QRFa—new patients) | 99.08 | 97.79 | 30.00 | 98.13 | 97.58 | 30.19 | |
| Sustained hypoglycemic events prediction (QRF—new time periods) | 98.54 | 98.57 | 22.36 | 97.72 | 98.49 | 22.44 | |
aQRF: quantile regression forest.