Machine Learning Methods for Predicting Syncope Severity in the Emergency Department: A Retrospective Analysis.

Background And Aims: Syncope is a frequent reason for hospital emergency admissions, presenting significant challenges in determining its cause and associated risks. Despite its prevalence, research on using artificial intelligence (AI) to improve patient outcomes in this context has been limited. The main objective of current study is to predict the severity of syncope cases using machine learning (ML) algorithms based on data collected during on-site treatment and ambulance transportation.