Background: This study aims to get an effective machine learning (ML) prediction model of
new-onset postoperative atrial fibrillation (POAF) following coronary artery bypass grafting …

Postoperative atrial fibrillation (POAF) occurs in up to 20% to 55% of patients who
underwent cardiac surgery. Machine learning (ML) has been increasingly employed in …

Objectives This study aimed to use machine learning algorithms to build an efficient
forecasting model of atrial fibrillation after cardiac surgery, and to compare the predictive …

Some patients with postoperative atrial fibrillation (POAF) after non-cardiac surgery need
treatment, and a predictive model for these patients is clinically useful. Here, we developed …

Background: New-onset postoperative atrial fibrillation (POAF) is the most common
complication after valvular surgery, but its etiology and risk factors are incompletely …

Objective To select variables associated with new-onset postoperative atrial fibrillation
(POAF) following isolated coronary artery bypass grafting (CABG) and develop a nomogram …

Background This cohort study collected the clinical data of patients who underwent off-pump
coronary artery bypass grafting (OPCABG) during hospitalization to observe the occurrence …

Background New onset postoperative atrial fibrillation (POAF) is the most common
complication of cardiac surgery, with an incidence ranging from 15 to 50%. This study aimed …

The objective of this study was to identify and evaluate predictors of postoperative atrial
fibrillation (POAF) in a large coronary artery bypass grafting (CABG) cohort. This was a …

Background: Postoperative atrial fibrillation (POAF) after cardiac surgery has great clinical
and economic implications. Many attempts have been made to identify risk factors aiming at …