Machine learning models, including Random Forest and Support Vector Machine (SVM), were applied to select potential AF-related diagnostic biomarkers, and validated in the animal model (beagles; <i>n</i> = 6).<h4>Results</h4>A total of 5,648 DEGs were identified, including six lactylation-related genes (DDX39A, ARID3A, TKT, NUP50, G6PD, and VCAN). This evidence concerns the gene ARID3A and atrial fibrillation.