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Fig. 4 | BMC Medical Informatics and Decision Making

Fig. 4

From: Machine learning-based risk models for procedural complications of radiofrequency ablation for atrial fibrillation

Fig. 4

Top-ranked features in predicting different complications. A: Top-ranked 10 features derived from the RF model in predicting any complication; B: Top-ranked 5 features derived from the XGBoost model in predicting cardiac effusion/tamponade; C: Top-ranked 10 features derived from the RF model in predicting hemorrhage; D: 13 important features in predicting any complication, cardiac effusion/tamponade or hemorrhage

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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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