8 papers
Validation of an AI-based end-to-end model for prostate pathology using long-term archived routine samples
Xiaoyi Ji, Renata Zelic, Oskar Aspegren +11
Artificial intelligence (AI) is becoming a clinical tool for prostate pathology, but generalization across variations in sample preparation and preservation over prolonged time per…
AI-based Prediction of Biochemical Recurrence from Biopsy and Prostatectomy Samples
Andrea Camilloni, Chiara Micoli, Nita Mulliqi +11
Biochemical recurrence (BCR) after radical prostatectomy (RP) is a surrogate marker for aggressive prostate cancer with adverse outcomes, yet current prognostic tools remain imprec…
Validation of Diagnostic Artificial Intelligence Models for Prostate Pathology in a Middle Eastern Cohort
Peshawa J. Muhammad Ali, Navin Vincent, Saman S. Abdulla +8
Background: Artificial intelligence (AI) is improving the efficiency and accuracy of cancer diagnostics. The performance of pathology AI systems has been almost exclusively evaluat…
The PAR dataset: Prostate biopsy whole slide images from an underrepresented Middle Eastern population
Peshawa J. Muhammad Ali, Navin Vincent, Saman S. Abdulla +8
Artificial intelligence (AI) is increasingly used in digital pathology. Publicly available histopathology datasets remain scarce, and those that do exist predominantly represent We…
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…
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…