BMC Medical Informatics and Decision Making

Table 6 Comparison of the classifier and features proposed in this study with the features proposed in previous study

From: Risk prediction of heart failure in patients with ischemic heart disease using network analytics and stacking ensemble learning

Classifier	Network Features	Metrics [Mean ± SD]
Classifier	Network Features	Precision	Recall	Accuracy	F₁ score	AUC
DXLR model	our study	0.723 ± 0.014	0.892 ± 0.012	0.857 ± 0.007	0.798 ± 0.010	0.934 ± 0.004
DXLR model	[37]	0.553 ± 0.017	0.649 ± 0.021	0.722 ± 0.009	0.597 ± 0.013	0.779 ± 0.010
Random Forest	our study	0.681 ± 0.015	0.833 ± 0.013	0.823 ± 0.007	0.749 ± 0.011	0.905 ± 0.005
Random Forest	[37]	0.532 ± 0.016	0.704 ± 0.016	0.710 ± 0.009	0.606 ± 0.013	0.781 ± 0.010

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ISSN: 1472-6947

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