Clinically-Informed Modeling for Pediatric Brain Tumor Classification from Whole-Slide Histopathology Images

ArXi:2604.21060v1 Announce Type: new Accurate diagnosis of pediatric brain tumors, starting with histopathology, presents unique challenges for deep learning, including severe data scarcity, class imbalance, and fine-grained morphologic overlap across diagnostically distinct subtypes. While pathology foundation models have advanced patch-level representation learning, their effective adaptation to weakly supervised pediatric brain tumor classification under limited data remains underexplored. In this work, we.