Onkológia 4/2026

Artificial intelligence in diagnosis and treatment of bladder cancer

Artificial Intelligence (AI) has become an integral part of our daily lives. In medicine, its potential lies in increasing the accuracy of diagnostics and personalizing the treatment of various diseases, including bladder cancer (BC). The introductory section of this review article outlines the evolution of AI from symbolic to generative approaches. The subsequent subsection focuses on studies that have tested and validated various AI models aimed at improving BC diagnostics within the fields of clinical biochemistry (metabolomics), radiology (radiomics), urology (e.g., the CystoNet system), and pathology (neural networks for digital tissue image analysis). The final part addresses AI-driven predictive models for patient survival and treatment response, including BCG therapy and neoadjuvant chemotherapy prior to radical cystectomy. Future developments in this field require the refinement of explainable AI (XAI) methods, the implementation of robust external validation, and seamless integration into clinical workflows, particularly through interoperability with existing hospital information systems.

Keywords: artificial intelligence, bladder cancer, digital pathology, explainable AI, clinical workflow