INTEGRATING AI DECISION-SUPPORT SYSTEMS IN RENAL SURGERY: ENHANCING ACCURACY AND PERIOPERATIVE OUTCOMES

Abstract

Renal surgery has evolved toward minimally invasive and nephron-sparing approaches, requiring complex, data-intensive decision-making to balance oncologic control with functional preservation. Artificial intelligence-based decision-support systems (AI DSS) have emerged as promising tools to augment clinical judgment by integrating multimodal data across the perioperative continuum. However, their clinical role, evidence base, and implementation challenges in renal surgery remain incompletely defined. This review aims to critically evaluate the current and emerging applications of AI decision support systems in renal surgery, with a focus on enhancing surgical accuracy and perioperative outcomes. A narrative review of recent literature was conducted, emphasising guideline-based management, AI methodologies, and clinical studies published between 2020 and 2025. Evidence was synthesised across preoperative, intraoperative, and postoperative phases of renal surgery, with attention to validation status, ethical considerations, and real-world implementation barriers. AI DSS demonstrate significant potential in preoperative risk stratification, tumour characterisation, and surgical planning; intraoperative guidance through computer vision, augmented reality, and robotic assistance; and postoperative complication prediction and outcome optimisation. Despite encouraging performance metrics, most AI models have been validated retrospectively, with limited prospective and multicentre evidence. Key challenges include data quality, model generalizability, explainability, regulatory oversight, and clinician acceptance. AI decision-support systems represent a powerful adjunct to contemporary renal surgery, offering opportunities to improve precision and perioperative outcomes. Realising their full clinical impact will require rigorous validation, ethical governance, and seamless integration into surgical workflows to ensure safe, equitable, and effective adoption.