Development and Validation of Machine Learning-Based Model for Hospital Length of Stay in Patients Undergoing Endovascular Interventional Embolization for Intracranial Aneurysms

This study comprehensively identified key predictive factors for prolonged LOS in patients with IA undergoing interventional embolization and confirmed the efficacy of an RF model for predicting prolonged LOS in patients with IA undergoing interventional embolization. The construction of the LOS prediction model may effectively optimize healthcare resource utilization, inform better clinical decision-making, and offer valuable prognostic insights.