Development of a new tool for prediction of hospital length of stay and intensive care needs in trauma patients using Machine Learning

Machine learning models trained on national trauma registry data demonstrated strong performance in predicting ICU admission and moderate accuracy in categorizing hospital length of stay. The XGB model showed the highest overall predictive power and may serve as a useful tool to support early triage, guide clinical decision-making, and optimize resource allocation in trauma care settings.