Table 3.

Models’ performance comparison of machine learning models based on routine vital signs monitoring without glucose.

Models	Accuracy, median (IQR)	Precision, median (IQR)	Recall, median (IQR)	F1-score, median (IQR)	AUROCa, median (IQR)
SVMb	0.61 (0.59-0.64)	0.61 (0.59-0.63)	0.57 (0.55-0.6)	0.59 (0.57-0.61)	0.69 (0.67-0.71)
Random forest	0.66 (0.65-0.68)	0.65 (0.62-0.67)	0.68 (0.66-0.71)	0.66 (0.64-0.69)	0.73 (0.72-0.74)
ExtraTrees	0.67 (0.65-0.7)	0.65 (0.63-0.67)	0.66 (0.65-0.68)	0.66 (0.65-0.67)	0.74 (0.72-0.76)
XGBoostc	0.67 (0.66-0.69)	0.65 (0.63-0.67)	0.73 (0.71-0.74)	0.68 (0.66-0.7)	0.72 (0.7-0.73)
AdaBoost	0.67 (0.66-0.69)	0.67 (0.65-0.68)	0.66 (0.64-0.68)	0.66 (0.65-0.67)	0.75 (0.74-0.77)
Logistic	0.64 (0.63-0.65)	0.63 (0.62-0.64)	0.63 (0.61-0.64)	0.63 (0.62-0.63)	0.69 (0.67-0.7)

^aAUROC: area under the receiver operating characteristic curve.

^bSVM: support vector machine.

^cXGBoost: Extreme Gradient Boosting.