Predicting the Course of Post-Traumatic Stress Following Emergency Room Admission: A Machine Learning Approach

High-dimensional data about n=338 Emergency Room patients (34.9% female and 65.1% male; mean age 37.21±13.37) has been collected and heterogeneous trajectories of Post-traumatic Stress Disorder through 6 months post-trauma using Latent Growth Mixture Modeling have been identified as well as risk factors applying Machine Learning algorithms.