An interpretable machine learning model for predicting mortality risk in adult ICU patients with acute respiratory distress syndrome

We developed a machine learning-based model for predicting the risk of death of critically ill ARDS patients in the ICU, and our model can effectively identify high-risk ARDS patients at an early stage, thereby supporting clinical decision-making, facilitating early intervention, and improving patient prognosis.