ReviewJournal of robotic surgery2026
Artificial intelligence and machine learning in robotic, teleoperated, and remote surgery: a bibliometric and knowledge mapping analysis (2015-2025).
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
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) and machine learning (ML) technologies are rapidly transforming telesurgery by enhancing robotic-assisted surgical systems, remote surgical communication, image-guided interventions, and intelligent decision-making. The integration of AI-driven algorithms with telesurgical platforms has accelerated research activity across medicine, robotics, engineering, and computer science. However, the global research landscape, collaborative structure, and emerging thematic trends of AI- and ML-enabled telesurgery remain insufficiently explored. Therefore, the present study aimed to perform a comprehensive bibliometric and knowledge mapping analysis of global research on AI and ML applications in robotic, teleoperated, and remote surgery published between 2015 and 2025. A bibliometric analysis was conducted using the Scopus database on 28 May 2026. Articles published between 2015 and 2025 related to AI, machine learning, robotic surgery, teleoperation, and telesurgery were retrieved using predefined search terms. Only English-language research articles were included. Bibliometric indicators including annual publication trends, citation analysis, leading journals, productive authors, institutions, funding agencies, country collaborations, co-citation analysis, and keyword co-occurrence analysis were evaluated. Visualization and network mapping were performed using VOSviewer software (version 1.6.20). A total of 2,201 publications were identified from 112 countries. Scientific output demonstrated substantial exponential growth, increasing from 85 publications in 2015 to 1,167 publications in 2025. Medicine (29%), computer science (24%), and engineering (20%) represented the dominant research areas. Journal of Robotic Surgery emerged as the leading publication source, while China and the United States were identified as the most influential contributing countries. Keyword co-occurrence analysis highlighted major research themes including robotic surgery, deep learning, machine learning, intelligent robotics, teleoperation, and minimally invasive surgery. Overlay visualization demonstrated a recent shift toward AI-driven autonomous systems, computer vision, surgical workflow analysis, and intelligent robotic platforms. Co-citation analysis further revealed strong interdisciplinary foundations involving surgical sciences, robotics, computer vision, and advanced deep learning methodologies. Research on AI and ML applications in robotic, teleoperated, and remote surgery has grown rapidly over the last decade and is increasingly characterized by strong interdisciplinary collaboration and technological innovation. Emerging trends suggest a transition from conventional robotic-assisted surgery toward intelligent, data-driven, and semi-autonomous telesurgical systems. The findings of this bibliometric study provide valuable insights into the evolving scientific landscape of intelligent telesurgery and may support future research, clinical translation, technological development, and policy planning in robotic-assisted remote surgical care.
Indexed as
Identifiers
42298236What Socratic 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 Socratic graph.