Machine learning-based early identification of heart failure/congestion complicating acute coronary syndrome using body composition analysis: a retrospective cohort study
Background Heart failure (HF) is a major complication of acute coronary syndrome (ACS) and is associated with poor outcomes. Aims To develop and internally evaluate a machine learning (ML) model for early identification/risk classification of HF or congestion among patients with ACS using bioelectrical impedance analys...