Evidence map›Paper›PMID 42667308›Full record

ReviewJournal of robotic surgery2026

Robotic-assisted bronchoscopy for lung cancer: bibliometric and visualized analysis.

Shuai Song, Binbin Zhan, Yu Wang

Abstract readReview
PubMed Publisher
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Shuai SongDepartment of Thoracic Surgery, Beijing Friendship Hospital, Capital Medical University, No.95 Yongan Road, Xicheng, Beijing, 100050, China.
Binbin ZhanDepartment of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, No.95 Yongan Road, Xicheng, Beijing, 100050, China.
Yu WangDepartment of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, No.95 Yongan Road, Xicheng, Beijing, 100050, China. wangyu926498301@163.com.ORCID https://orcid.org/0009-0001-9906-2468

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer ranks among the most prevalent malignancies worldwide, with a high mortality rate, and early diagnosis is crucial for improving patient outcomes. Robotic-assisted bronchoscopy (RAB) has attracted increasing attention from clinicians and researchers as an emerging diagnostic technology. This bibliometric analysis presents co‑occurrence networks based on 172 publications sourced from the Web of Science Core Collection (WoSCC) between 2019 and 2026. Data analysis and visualization were conducted using CiteSpace, VOSviewer, Scimago Graphica, Microsoft Excel, and R software with the Bibliometrix package. The number of publications increased markedly after 2023, and although the dataset for 2026 was incomplete, the publication count had already surpassed that of previous years. The collaboration network involved 25 nations, among which the United States provided the largest number of publications by a substantial margin, and Mayo Clinic was the most productive institution. Research on RAB in lung cancer has progressed through three developmental stages: technological exploration, clinical validation, and therapeutic expansion. The early focus on feasibility and technology introduction has shifted toward clinical treatment and comprehensive disease management. Recent research hotspots include radiofrequency ablation and atelectasis, among others. The present study offers a broad overview of the global research landscape, collaboration patterns, and new research trends in RAB for lung cancer, offering valuable insights into future technological advancements, interdisciplinary cooperation, and clinical translation.

Indexed as

BibliometricsBronchoscopyLung NeoplasmsRobotic Surgical ProceduresHumansBibliometricBronchoscopyLung cancerRobotic-assistedVisualization analysis

Identifiers

What Socratic 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 Socratic graph.