Fig. 3From: A weakly supervised deep learning model integrating noncontrasted computed tomography images and clinical factors facilitates haemorrhagic transformation prediction after intravenous thrombolysis in acute ischaemic stroke patientsIllustration of the accuracy in terms of ROC curves for WSDL model and HAT and SEDAN scores of HT based on NCCT imaging data and clinical informationBack to article page