Introduction and Purpose: Artificial intelligence (AI) is a revolutionary tool assisting diagnostics treatment, and prognosis of treatment outcomes in various medical fields, including urology. The purpose of this review is to outline contemporary uses of AI techniques in clinical urology and evaluate their effect on the quality of patient care, considering limitations and future research directions. State of Knowledge: AI uses in urology consist of, inter alia, evaluation of radiological and histopathological images (for example, in prostate cancer diagnosis), treatment prediction outcomes (e.g., bladder cancer), individualization of treatment, improvement in surgical planning decisions and assistance in perioperative care. Machine learning algorithms are applied to recognize pathological changes with high accuracy, often like the assessments of experts. Natural language processing (NLP) algorithms are utilized in the analysis of medical documentation and streamlining information flow. Despite quick development, complete integration of AI into daily clinical practice faces barriers related to data quality, model interpretability, and legal and ethical aspects. Summary: Artificial intelligence has excellent potential for enhancing diagnostic and therapeutic accuracy in urology. Nonetheless, additional clinical research, standardization and validation with multi-center datasets are required. The appropriate implementation of AI in urological practice can lead to personalized, more efficient patient management.
Zagórski et al. (Wed,) studied this question.