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 …

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 …

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

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 …

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 …

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) is defined as the atrial fibrillation (AF) induced during
the postoperative phase. POAF has been recognized as a benign and transient AF. 1 …

Background Postoperative atrial fibrillation (POAF) is associated with an increase in
morbidity and mortality. We aimed to develop and validate a simple clinical model for the …

Objective (s) Using the Medical Information Mart for Intensive Care III (MIMIC-III) database,
we compared the performance of machine learning (ML) to the to the established gold …

New-onset postoperative atrial fibrillation (POAF) is the most common arrhythmia in patients
undergoing cardiac or thoracic surgery, resulting in adverse consequences such as …