Development and validation of machine learning prediction model based on computed tomography angiography–derived hemodynamics for rupture status of intracranial aneurysms: a Chinese multicenter study
Decisions regarding the optimal management of unruptured intracranial aneurysms (UIAs) depend on a comprehensive comparison of the risks between aneurysm rupture and interventional treatment. The accurate prediction for UIA rupture risk is important for clinicians and patients. Our study further proves that the hemodynamic parameters can improve prediction performance for rupture status of UIAs. Moreover, the AUC of model integrating