Artificial intelligence in bladder cancer management: a narrative review of diagnostic and surgical advances and current limitations.

INTRODUCTION

Bladder cancer (BC) is associated with high recurrence and progression rates that require intensive surveillance. In this context, Artificial Intelligence (AI) offers promising tools to enhance diagnostic, prognostic, and surgical pathways.

AREAS COVERED: This narrative review critically examines the current state of AI applications across the bladder cancer care focusing on diagnostic, prognostic and surgical domains. A comprehensive literature search was conducted to identify relevant studies. Key topics include radiomics in computed tomography (CT) and magnetic resonance imaging (MRI), radiogenomics, pathomics and AI-assisted cystoscopy. Furthermore, the role of AI in preoperative planning, intraoperative navigation and surgical training is discussed highlighting its integration in robotic and endoscopic procedures.

EXPERT OPINION: AI is rapidly redefining bladder cancer management through multimodal data integration and predictive modeling. While current evidence demonstrates high diagnostic and prognostic performance, clinical implementation remains limited by heterogeneity, lack of standardization and insufficient external validation. Future efforts should prioritize prospective validation, explainability and integration into clinical workflows to realize AI's full potential in personalized uro-oncology.