Jie Yang

Development and validation of an interpretable machine learning model for early prediction of postoperative atrial fibrillation following on-pump cardiac surgery

Background Postoperative atrial fibrillation (POAF) complicates 20%–40% of cardiac surgeries, increasing morbidity, length of stay, and healthcare costs. Early risk stratification could enable targeted prophylactic interventions. This study aimed to develop and validate an interpretable machine learning model for predi...