Integrating traditional statistics and explainable machine learning for risk stratification of atrial fibrillation recurrence after pulsed field ablation: a hypothesis-generating single-center study.

The AUC of the exploratory Random Forest model (0.697) was numerically higher than that of CAAP-AF (0.551) and ATLAS (0.540), though DeLong’s test indicated that these differences did not reach statistical significance (both P > 0.05), further underscoring the preliminary and exploratory nature of our performance comparisons.

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