Prostate cancer (PCa) is a common malignancy in males. The pathology review of PCa is
crucial for clinical decision-making, but traditional pathology review is labor intensive and …

In this modern era of digital pathology, artificial intelligence (AI)-based diagnostics for
prostate cancer has become a hot topic. Multiple retrospective studies have demonstrated …

Objectives The high incidence of prostate cancer causes prostatic samples to significantly
affect pathology laboratories workflow and turnaround times (TATs). Whole-slide imaging …

Background Artificial intelligence (AI) is a promising tool in pathology, including cancer
diagnosis, subtyping, grading, and prognostic prediction. Methods The aim of the study is to …

Importance The Gleason grading system has been the most reliable tool for the prognosis of
prostate cancer since its development. However, its clinical application remains limited by …

Multiple novel modalities tasking artificial intelligence based computational pathology
applications and integrating other variables, such as risk factors, tumor microenvironment …

Abstract Background Prostate cancer (PCa) is the most frequently diagnosed cancer in men
worldwide, affecting around 1.4 million individuals. Current PCa diagnosis relies on …

The diagnosis of prostate cancer (PCa) depends on the evaluation of core needle biopsies
by trained pathologists. Artificial intelligence (AI) derived models have been created to …

Artificial intelligence (AI) has shown promise for diagnosing prostate cancer in biopsies.
However, results have been limited to individual studies, lacking validation in multinational …

Background A definitive diagnosis of prostate cancer requires a biopsy to obtain tissue for
pathologic analysis, but this is an invasive procedure and is associated with complications …