Early Prediction of ICU Hypotension Using Machine Learning

This prospective observational study aims to develop and internally validate a machine learning model for the early prediction of hypotension in adult intensive care unit patients. The model will use routinely collected non-invasive vital signs, heart rate, medication-dose records, and fluid-balance data recorded during standard ICU care. No intervention will be assigned by the study, and patient management will not be changed according to the model output. The primary aim is to predict hypotension 30 minutes before its occurrence; shorter 5- and 15-minute prediction horizons will also be evaluated.