Machine Learning–Based Rupture Risk Prediction for Intracranial Aneurysms: A Systematic Review and Meta-Analysis

ML techniques have the potential to enhance the prediction of intracranial aneurysm rupture compared with traditional approaches, like the PHASES score. Incorporating hemodynamic parameters may further enhance the accuracy of ML models. Feature prospective studies are required to validate the utility of ML models for clinical integration.