Table 2.

Comparison of the model’s performance metrics with different machine learning classifiers.

	Logistic regression	Support vector classifier	Decision tree	Random forest	Gaussian naïve Bayes	Best score
Accuracy	0.91	0.90	0.84	0.90	0.82	Logistic regression
Precision	0.81	0.81	0.55	0.80	0.50	Logistic regression
Recall (sensitivity)	0.64	0.59	0.58	0.59	0.68	Gaussian naïve Bayes
F1 score	0.71	0.68	0.56	0.67	0.58	Logistic regression
AUROC	0.76	0.72	0.65	0.70	0.67	Logistic regression