Global research landscape of robot-assisted surgical training: a 35-year bibliometric and visualization analysis

Over 17 million robot-assisted surgeries (RAS) have been performed globally, driving demand for standardized and effective surgical training. This study maps the 35-year bibliometric landscape of RAS training research to identify trends, gaps, and future directions.

We analyzed 592 publications from the Web of Science Core Collection (1990-2025) using CiteSpace, VOSviewer, and Excel. Metrics included publication trends, citations, author/institutional collaborations, journal impact, keyword clusters, and burst detection.

Research output grew exponentially, with three evolutionary phases: (1) Technical validation (1998-2010), focusing on prostatectomy and lymphadenectomy; (2) Methodological innovation (2011-2020), emphasizing face and simulator (e.g., Fundamentals of Robotic Surgery); and (3) Standardization/AI integration (2020-2025), prioritizing patient safety and training curriculum. The USA dominated contributions (47.13% of publications), followed by the UK (highest citations/article: 33.43) and Germany. Surgical Endoscopy published the most studies (70), while European Urology had the highest impact (IF: 25.2), The Journal of Robotic Surgery is promising. The analysis identifies three critical challenges currently facing the field: (1) skill transfer from training to clinical practice, (2) integration of artificial intelligence technology, and (3) establishment of a standardized governance framework empowered by AI for robotic surgery training.

RAS training research still focuses on European and North American countries, with differences in global cooperation and standardized training governance. Future efforts require cross-border partnerships, open access policies, and governance frameworks to coordinate training standards and accelerate the integration of artificial intelligence technology and enhance clinical translation of simulated training results.