Table 5.
Performance of the quantile regression forest model at different thresholds and the average time to predict a hypoglycemic event.
| Metric | 30-minute prediction horizon | 60-minute prediction horizon | |||||
|
|
Threshold 1 | Threshold 2 | Threshold 3 | Threshold 1 | Threshold 2 | Threshold 3 | |
| Sensitivity (%) | 98.54 | 99.27 | 99.51 | 97.72 | 98.29 | 98.99 | |
| Specificity (%) | 98.57 | 97.56 | 96.68 | 98.49 | 97.06 | 95.53 | |
| False alerts (n) | 6932 | 11,960 | 16,049 | 7215 | 14,027 | 21,297 | |
| False alerts with transient events as positives (n) | 3736 | 8149 | 12,007 | 3974 | 9956 | 16,775 | |
| False alert rate (%) | 22.36 | 35.36 | 43.34 | 22.44 | 37.19 | 46.96 | |
| Average time to predict an event (minutes) | 18.78 | 22.95 | 26.51 | 25.24 | 35.08 | 48.35 | |