Dan-Dan Geng

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

An interpretable machine learning model for POAF prediction developed and temporally validated in a single-center cohort may serve as a candidate decision-support tool for early ICU risk stratification, pending prospective multicenter validation of its generalizability and clinical utility.