Artificial Intelligence and Digital Health in Urology

This chapter explores the integration of machine learning, deep learning, and natural language processing into urological practice, covering applications in diagnostic imaging, pathological grading, surgical video analytics, and clinical decision support. It critically evaluates the performance of AI algorithms in prostate cancer detection on multiparametric MRI, bladder cancer diagnosis on cystoscopy, and renal mass characterization, benchmarking against conventional radiological and clinical standards. Ethical considerations, data governance, algorithmic bias, regulatory frameworks, and the pathway to clinical implementation of AI tools in urology are discussed.