Artificial intelligence–driven digital pathology in urological cancers: current trends and future directions

Abstract

Artificial intelligence (AI) in digital pathology has gained attention owing to its potential in urological cancer diagnosis and management. This review highlights AI's applications and challenges in three major urological cancers. Prostate cancer studies have demonstrated reliable diagnostic performance and promising prognosis prediction. Renal cancer study shows potential but faces challenges in generalizability and prognosis. Bladder cancer studies are limited by the lack of large-scale datasets. Despite of these active studies, challenges remain regarding data availability, prognosis, and generalizability. Future efforts should emphasize multimodal approaches and multi-institutional collaboration with larger datasets to fully realize the potential of AI in urological cancers.

Ähnliche Arbeiten