Artificial intelligence in surgical oncology: A comprehensive review from preoperative planning to postoperative care

Abstract

While artificial intelligence (AI) has demonstrated significant potential across medical fields, its surgical applications remain largely exploratory. This review synthesizes recent advances in AI technologies and their clinical integration within surgery. Preoperatively, AI enhances planning by improving risk prediction accuracy, refining imaging analysis, and enabling virtual surgical training, thereby optimizing surgical preparation and safety. Intraoperatively, it facilitates real-time navigation, powers robotic assistance, enables 5 G telesurgery, and provides decision support, contributing to enhanced precision and procedural efficiency. Postoperatively, AI-driven monitoring and remote care optimize recovery pathways and complication management, improving outcomes and resource utilization. Despite these advancements, key challenges persist, including data bias, the “black-box” problem, privacy concerns, model generalizability, and real-time processing constraints. Interdisciplinary collaboration, robust ethical frameworks, and sustained technical refinement are essential to fully realizing AI’s potential. Future progress, driven by technological evolution and deeper multidisciplinary cooperation, is poised to advance the practice of surgical oncology toward greater precision, intelligence, and accessibility, thereby fostering innovation in global healthcare systems.