ReviewJournal of robotic surgery2026
Artificial intelligence, surgical vision, and digital navigation in robotic urology: a bibliometric and knowledge-mapping analysis.
Review in Journal of robotic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital technologies are increasingly used to extend the anatomical, functional, and procedural information available in robot-assisted urology, but their development has not been examined within a common field-level framework. The final corpus comprised 297 English-language articles and reviews from the Web of Science Core Collection after prespecified screening. We examined publication trends, collaboration patterns, citation relationships, author-keyword structures, and six mutually exclusive primary technology domains using R, VOSviewer, and CiteSpace. Annual output rose from 12 publications in 2018 to 52 in 2025. The primary domain encompassing three-dimensional modelling, augmented reality, mixed reality, and digital navigation was the largest, comprising 118 of 297 publications. Surgical vision, video, and workflow intelligence showed the clearest recent expansion, accounting for 24.0% of publications in 2022-2026, while artificial intelligence and machine learning (AI/ML) prediction and decision support increased from 5.7% in 2018-2021 to 10.4% in 2022-2026. Research was concentrated in the USA, Italy, and the Netherlands, with distinct country-level technology profiles. Co-citation and keyword analyses situated newer work in surgical-phase recognition and artificial intelligence alongside established research on navigation, fluorescence and molecular guidance, image-guided surgery, and performance analytics. These patterns suggest that the field is diversifying by adding data-driven interpretation of intraoperative information to established systems of planning, guidance, and performance assessment. They describe research activity and knowledge structure rather than clinical effectiveness, technological maturity, or readiness for routine use.
Indexed as
Identifiers
42579258What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.