Development and Validation of Deep Learning Model for Predicting Long-Term Prognosis in Patients with Symptomatic Intracranial Arterial Stenosis

Compared to logistic regression, the deep learning model exhibited significantly improved predictive accuracy for the risk of progression in symptomatic ICAS patients. The high performance and reliability of the deep learning model highlight its potential clinical utility in predicting ICAS progression, ultimately aiding in risk stratification and personalized treatment strategies.