Atrial fibrillation identification in patients with non-alcoholic fatty liver disease: a machine learning model based on immune-inflammatory markers

This study constructed and validated a machine learning model integrating multiple immune inflammatory markers for effectively identifying the risk of atrial fibrillation in patients with NAFLD. The SVM model exhibited excellent discriminatory ability and clinical applicability. The developed web tool aids in the identification of high-risk individuals and offers new strategies for preventive interventions against AF.