A Gradient-Boosted Decision-Tree Algorithm for the Prediction of Short-Term Mortality in Acute Heart Failure Patients
Background: Acute heart failure (AHF) is associated with significant morbidity and mortality. Effective patient risk stratification is essential to guiding hospitalization decisions and clinical management. Clinical decision support systems can be used to improve mortality predictions in emergency care settings.