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Artificial intelligence, surgical vision, and digital navigation in robotic urology: a bibliometric and
Gongping Wu1,2,3, Hanlin Liu1,2,3, Debo Li1,2,3
1Department of Urology, Lanzhou University Second Hospital, No.82 Cuiyingmen, Lanzhou, 730030, China.
Journal of Robotic Surgery
|August 11, 2026
Summary
Digital technologies in robot-assisted urology are rapidly expanding, with 3D modeling and AR/MR leading growth. Artificial intelligence and machine learning show increasing adoption for enhanced surgical insights and decision support.
Area of Science:
- Urology
- Medical Technology
- Computer Science
Background:
- Digital technologies enhance robot-assisted urology with anatomical, functional, and procedural data.
- Field-level frameworks for these developments are lacking.
- Understanding technology trends is crucial for future advancements.
Purpose of the Study:
- To analyze publication trends and knowledge structure in digital technologies for robot-assisted urology.
- To identify key technology domains and collaboration patterns.
- To map the evolution and diversification of the field.
Main Methods:
- Bibliometric analysis of 297 articles from Web of Science Core Collection.
- Utilized R, VOSviewer, and CiteSpace for trend, collaboration, and keyword analysis.
- Examined six primary technology domains and country-level research profiles.
Main Results:
- Annual publication output increased from 12 (2018) to 52 (2025).
- 3D modeling, AR/MR, and digital navigation formed the largest domain (118 publications).
- Surgical vision/workflow intelligence and AI/ML showed significant recent expansion.
- Research concentrated in USA, Italy, and Netherlands with distinct technology specializations.
Conclusions:
- The field is diversifying, integrating data-driven intraoperative information interpretation.
- New research in surgical-phase recognition and AI complements established areas like navigation and performance analytics.
- Findings describe research activity and knowledge structure, not clinical effectiveness or readiness for routine use.
