The Evolving Landscape of Urology in the Era of Artificial Intelligence: An Update of Clinical Applications and Emerging Innovations.

Artificial intelligence (AI) has revolutionized urology, offering transformative advancements in diagnostics, treatment planning and patient care. This update highlights AI applications in diagnostic imaging, benign urological conditions, uro-oncology, urologic surgeries and patient monitoring. AI algorithms including machine learning (ML) and deep learning (DL) enhance non-oncological applications include predicting ureteral stone passage (accuracy: 85%) and optimizing benign prostatic hyperplasia (BPH) management. In uro-oncology, AI predicts biochemical recurrence post-prostatectomy (accuracy: 95%) and stratifies renal cell carcinoma aggressiveness and prostate cancer detection via MRI analysis (AUC: 0.95-0.99) and improve bladder cancer diagnosis through cystoscopic image classification (sensitivity: 89.7%). Robotic surgery benefits from AI-driven precision in procedures like robot-assisted radical prostatectomy (RARP). AI enables early detection of minimal residual disease and recurrence through analysis of urinary 'liquid biopsies', while AI-based 'computational biopsy' predicts genomic markers and clinical risk scores directly from H&E-stained slides, reducing costs and turnaround time. Ethical challenges including algorithmic bias and data privacy necessitate robust governance frameworks. Future innovations, such as artificial general intelligence (AGI), federated learning, promise personalized care and autonomously diagnoses and prescribes treatments of urologic illnesses but require interdisciplinary collaborations. This review underscores AI's potential to improve outcomes while addressing limitations in data diversity and clinical integration.