Evidence map›Paper›PMID 40906002›Full record

SynthesisJournal of robotic surgery2025

Technological evolution and research frontiers of robot-assisted ultrasound examination: a bibliometric exploration.

Xia Li, Zhen Hu, Chujun Wang, Shuangyi Cao, Chunquan Zhang

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Journal of robotic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Xia Li *Department of Ultrasound, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, No. 1, Minde Road, Donghu District, Nanchang, Jiangxi, 330006, People's Republic of China.
Zhen Hu *Department of Ultrasound, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, No. 1, Minde Road, Donghu District, Nanchang, Jiangxi, 330006, People's Republic of China.
Chujun WangDepartment of Ultrasound, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, No. 1, Minde Road, Donghu District, Nanchang, Jiangxi, 330006, People's Republic of China.
Shuangyi CaoDepartment of Ultrasound, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, No. 1, Minde Road, Donghu District, Nanchang, Jiangxi, 330006, People's Republic of China.
Chunquan ZhangDepartment of Ultrasound, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, No. 1, Minde Road, Donghu District, Nanchang, Jiangxi, 330006, People's Republic of China. jxzcq@163.com.

Funding

Jiangxi Society for Science Education Key Projects for Graduate Students in Schools 2025KXJYS033the Intramural Funding Project of the Second Affiliated Hospital of Nanchang University 2023efyC03the Key R&D Program of Jiangxi Province, China 20223BBG71005
6 · The paper itself

Abstract

Technological innovations in robot-assisted ultrasound (RAUS) have remarkably advanced the development of precision and intelligent medical imaging diagnosis. This study aims to use bibliometric methods to systematically analyze the technological evolution and research frontiers in the RAUS field, providing valuable insights for future research. This study used the Web of Science Core Collection database to retrieve English-language research papers and reviews related to RAUS published between 2000 and 2024. Using analytical tools such as R (with the Bibliometrix package), VOSviewer, and CiteSpace, the study conducted a bibliometric analysis from multiple angles, including literature distribution, collaboration networks, and knowledge clustering. The visualization of analysis results comprehensively revealed the hot topics and emerging research frontiers within the RAUS field. The results reveal an exponential growth trend in RAUS research, with China leading in publication output (accounting for 28.51% of total publications), while the USA leads in terms of citation impact and international collaboration networks. Institutions such as Johns Hopkins University and Chinese Academy of Sciences emerge as highly productive core contributors. The research field has formed a multidimensional interdisciplinary landscape encompassing "mathematical sciences-engineering technology-medical health." The focus is on the integration of artificial intelligence (AI) and its clinical application translation. From 2000 to 2014, the development of "mobile robots" laid the cornerstone for further advancements. From 2015 to 2018, research focused on the development of "surgery" and "tumors" for medical applications. From 2019 to 2024, the core focus will be on "medical robots and systems," "artificial intelligence" and "robotic ultrasound," highlighting the transformation of technology into an AI-driven model. This study systematically reviewed the development of RAUS through bibliometric methods, enriching academic understanding of the field and providing valuable guidance for future technological iterations, clinical translation, and global cooperation to ultimately achieve precision medicine and balanced medical resources.

Indexed as

BibliometricsRobotic Surgical ProceduresArtificial IntelligenceHumansUltrasonographyBibliometricsRobotRobot-assisted ultrasoundVisual analysis

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.