Table 3 The performance comparison of different models.

Model	Feature set	F1 score	Accuracy	Precision	Sensitivity	Specificity
Support vector machine	A2	0.508	0.786	0.889	0.356	0.980
Support vector machine	B2	0.748	0.800	0.614	0.956	0.730
Decision tree classifier	A2	0.043	0.697	1.000	0.022	1.000
Decision tree classifier	B2	0.667	0.745	0.561	0.822	0.710
Random forest classifier	A2	0.043	0.697	1.000	0.022	1.000
Random forest classifier	B2	0.747	0.828	0.685	0.822	0.830
Logistic regression	A2	0.333	0.752	1.000	0.200	1.000
Logistic regression	B2	0.677	0.724	0.532	0.933	0.630
Naive Bayes classifier	A2	0.851	0.910	0.881	0.822	0.949
Naive Bayes classifier	B2	0.800	0.848	0.677	0.978	0.790

Feature set A2: Features from feature set A1 retained after MI + LASSO dimensionality reduction. Feature set B2: Features from feature set B1 retained after MI + LASSO dimensionality reduction.

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