Artificial intelligence in urological malignancy diagnosis and prognosis: current status and future prospects
Mingwei Zhan1,#, Zhaokai Zhou2,#, Jianpeng Zhang3,#, Xin Wang4, Canxuan Li5, Bochen Pan6, Zhanyang Luo7, Wenjie Shi8, Yongjie Wang9, Minglun Li10, Weizhuo Wang11,*, Run Shi12,*, Jingyu Zhu1,13,*
Canadian Journal of Urology, Vol.33, No.1, pp. 35-49, 2026, DOI:10.32604/cju.2026.076084
- 28 February 2026
Abstract Artificial intelligence (AI) is transforming the diagnostic landscape of malignant tumors in the urinary system, including prostate cancer, bladder cancer, and renal cell carcinoma (RCC). By integrating imaging, pathology, and molecular data, AI enhances the precision and reproducibility of tumor detection, grading, and risk stratification. In prostate cancer, AI-assisted multiparametric Magnetic resonance imaging (MRI) and digital pathology systems improve lesion localization and Gleason scoring. For bladder cancer, deep learning-based cystoscopy and radiomics models from Computed tomography/magnetic resonance imaging (CT/MRI) enable real-time lesion segmentation and non-invasive biomarker prediction, such as Programmed Cell Death-Ligand 1 (PD-L1) expression. More >