Table 4.

Performance of the machine learning approaches for the estimation of 1-year all-cause readmission.

Model	AUCa	Accuracy	Precision	Recall	F1	Brier score
LRb	0.63	0.57	0.57	0.59	0.58	0.24
RFc	0.91	0.82	0.83	0.81	0.82	0.13
SVMd	0.96	0.90	0.86	0.96	0.91	0.16
ANNe	0.82	0.74	0.74	0.75	0.74	0.18
XGBoostf	0.92	0.83	0.82	0.84	0.83	0.12

^aAUC: area under the curve.

^bLR: logistic regression.

^cRF: random forest.

^dSVM: support vector machine.

^eANN: artificial neural network.

^fXGBoost: extreme gradient boosting.