Vision-Core Guided Contrastive Learning for Balanced Multi-modal Prognosis Prediction of Stroke

ArXi:2605.14710v1 Announce Type: new Deep learning and multi-modal fusion have nstrated transformative potential in medical diagnosis by integrating diverse data sources. However, accurate prognosis for ischemic stroke remains challenging due to limitations in existing multi-modal approaches. First, current methods are predominantly confined to dual-modal fusion, lacking a framework that effectively integrates the trifecta of medical images, structured clinical data, and unstructured text.