Artificial intelligence and surgical data science in robot-assisted radical prostatectomy: global research trends, knowledge structure, and emerging frontiers.

To systematically characterize the global research trends, knowledge structure, thematic hotspots, and frontier evolution of artificial intelligence (AI) and surgical data science in robot-assisted radical prostatectomy (RARP). The Web of Science Core Collection (WoSCC) was used as the data source. A comprehensive search was performed for studies related to robot-assisted radical prostatectomy, artificial intelligence, machine learning, deep learning, computer vision, surgical video analysis, surgical skill assessment, outcome prediction, and decision support. The search was conducted up to July 1, 2026. English-language Articles and Reviews were included. Conference abstracts, proceedings papers, editorials, letters, corrections, studies unrelated to RARP, publications involving robotic surgery without AI or intelligent algorithmic components, and records with incomplete bibliographic information were excluded. RStudio was used for data cleaning and annual publication trend analysis, while CiteSpace and VOSviewer were applied to construct and visualize collaboration networks, co-citation networks, keyword co-occurrence patterns, clustering maps, timeline views, time-zone maps, and citation burst analyses. A total of 311 original records were retrieved, of which 217 publications were ultimately included, comprising 195 Articles and 22 Reviews. Annual publication trends indicated that the field has undergone three developmental stages: an early low-output exploratory phase, an accelerated growth phase after 2018, and a rapid expansion phase after 2023. The number of publications peaked at 36 in 2025, while 28 publications were recorded in 2026 because the search year was still ongoing. At the country/region level, the United States, Italy, China, Japan, and England ranked among the leading contributors. At the institutional level, the University of Southern California, University of London, King's College London, Guy's & St Thomas' NHS Foundation Trust, and the Netherlands Cancer Institute made substantial contributions. Author and journal analyses identified Hung AJ as the most productive author, while the Journal of Robotic Surgery, BJU International, and the Journal of Endourology were the major publication outlets. Keyword co-occurrence and burst analyses suggested that research themes have gradually shifted from early topics such as "experience," "learning curve," "robotic prostatectomy," and "surgical skills" toward "validation," "performance," "artificial intelligence," "risk," "quality of life," "recovery," and "deep learning." AI and surgical data science are reshaping RARP research, driving the field from robot-assisted surgical performance toward data-driven surgical intelligence. Future studies should prioritize the development of multicenter, standardized surgical video and robotic platform datasets; strengthen model interpretability, external validation, and prospective clinical evaluation; and facilitate the translation of AI-assisted preoperative planning, intraoperative recognition, surgical skill assessment, and patient outcome prediction into real-world clinical workflows.