Predicting hemorrhagic transformation in acute ischemic stroke using a machine learning model based on clinical and HR-MRI features
Early prediction of hemorrhagic transformation (HT) in acute ischemic stroke (AIS) is critical for clinical decision-making. We aimed to develop and externally validate a highly interpretable machine learning model integrating high-resolution magnetic resonance imaging (HR-MRI) and clinical features to predict HT in pa...