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. 2021 Apr 29;6(2):e26909. doi: 10.2196/26909

Table 3.

Comparison of model performance based on sensitivity, specificity, and false alerts with patient-based and time-based validation for 30-minute and 60-minute prediction horizons (PHs).

Metrics Patient-based validation Time-based validation

30-minute PH 60-minute PH 30-minute PH 60-minute PH

Method 1: RFa Method 2: QRFb Method 1: RF Method 2: QRF Method 1: RF Method 2: QRF Method 1: RF Method 2: QRF
Sensitivity, % (SD) 39.11 (2.25) 99.09 (0.16) 49.27 (3.03) 97.61 (0.41) 96.17 98.94 95.34 97.91
Specificity, % (SD) 98.65 (0.09) 98.19 (0.10) 98.63 (0.12) 98.09 (0.11) 98.3 98.29 97.95 98.20
False alerts, n (SD)








Considering transient and nonhypoglycemic events as false 6936 (356) 9339 (459) 7043 (317) 9672 (431) 6476 8211 7346 8465

Considering only nonhypoglycemic events as false 3907 (200) 5368 (162) 4109 (156) 5677 (201) 3324 4531 4334 4799
False alert rate, % (SD) 26.32 (2.56) 26.50 (2.41) 26.44 (2.37) 26.36 (2.57) 22.79 23.86 26.41 23.79

aRF: random forest.

bQRF: quantile regression forest.