ArticleJournal of robotic surgery2025
Global bibliometric analysis of molecular imaging-guided robotic-assisted surgery: publication dynamics, thematic evolution, authorship patterns, and disciplinary landscape development (1982-2025).
Article in Journal of robotic surgery, 2025. 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
11 authors.
Funding
Abstract
Molecular imaging-guided robotic-assisted surgery (MIRS) represents a transformative convergence of imaging, robotics, and computational intelligence. Although the field is rapidly advancing, global research patterns and thematic progression remain insufficiently characterized. This study provides a comprehensive bibliometric evaluation to delineate the knowledge structure, conceptual transitions, and emerging research frontiers within MIRS. Total of 2984 Scopus-indexed documents (1982–2025) were analyzed using Bibliometrix and VOSviewer. Quantitative indicators, Lotka’s and Bradford’s laws, co-authorship networks, keyword co-occurrence, and Callon’s centrality–density mapping were applied to identify collaboration patterns, core publication sources, influential authors, and thematic evolution. The MIRS literature showed exponential growth (15.18% annual rate), with 55.2% of all publications produced between 2021–2025. The United States led in productivity (1056 documents; 24,909 citations), followed by China, the United Kingdom, Italy, and Germany, collectively accounting for 51.6% of total citations. Lotka’s Law confirmed a highly skewed authorship pattern, with < 1% of researchers producing more than ten papers. Bradford’s Law identified 20–30 core journals, including the Journal of Robotic Surgery and International Journal of Surgery. Keyword networks emphasized dominant themes—robotic surgery, image-guided surgery, indocyanine green—and highlighted emerging integration of artificial intelligence and deep learning. Collaboration analysis revealed eight major clusters, largely Western-centric. Thematic mapping demonstrated a shift from foundational robotic and imaging techniques toward computationally enhanced, semi-autonomous surgical systems. This study underscores the rapid maturation, technological convergence, and expanding interdisciplinarity of MIRS. The progression toward AI-augmented, data-driven precision surgery signals an upcoming paradigm shift, guiding future research toward automation, intelligent navigation, and more equitable global collaboration.
Indexed as
Identifiers
41372584What 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.