3 papers
cs.CV2025
Finding Holes: Pathologist Level Performance Using AI for Cribriform Morphology Detection in Prostate Cancer
Kelvin Szolnoky, Anders Blilie, Nita Mulliqi +23
Background: Cribriform morphology in prostate cancer is a histological feature that indicates poor prognosis and contraindicates active surveillance. However, it remains underrepor…
cs.CV2025
Artificial Intelligence-Assisted Prostate Cancer Diagnosis for Reduced Use of Immunohistochemistry
Anders Blilie, Nita Mulliqi, Xiaoyi Ji +13
Prostate cancer diagnosis heavily relies on histopathological evaluation, which is subject to variability. While immunohistochemical staining (IHC) assists in distinguishing benign…
cs.CV2025
Foundation Models -- A Panacea for Artificial Intelligence in Pathology?
Nita Mulliqi, Anders Blilie, Xiaoyi Ji +28
The role of artificial intelligence (AI) in pathology has evolved from aiding diagnostics to uncovering predictive morphological patterns in whole slide images (WSIs). Recently, fo…