Stroke is a leading cause of death and disability worldwide, making early diagnosis and intervention critical. In a recent study published in IEEE Access, our team introduced a groundbreaking end-to-end approach to stroke imaging analysis, combining effective connectivity modeling with interpretable artificial intelligence (AI). This innovation has the potential to transform clinical workflows by enhancing both the accuracy and transparency of stroke diagnoses, highlighting information and flow changes in areas that should be targeted by therapies such as stem cells.