arXiv cs.AI
· Papers
Towards Cellular-Scale Interpretability in Pathology Foundation Models for Biomarker Assessment
arXiv:2511.05150v2 Announce Type: replace-cross Abstract: Molecular biomarker testing in pathology is often costly and tissue-consuming, limiting scalable clinical deployment. Artificial intelligence applied to hematoxylin and eosin (HE)-stained histology could enable rapid biomarker screening, but clinical translation