ArticleERJ open research2026
An autonomous bronchoscopy robot controlled by artificial intelligence (BronchoBot) outperforms experienced bronchoscopists in a simulated setting.
Article in ERJ open research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.
What it found
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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.
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Who cites it
3 citing papers in PubMed.
- Artificial intelligence and digital health in bronchoscopy: advances in diagnostic accuracy, real-time navigation and procedural skills training.Breathe (Sheffield, England) · 2026Review
- Robotic-assisted bronchoscopy for lung cancer: bibliometric and visualized analysis.Journal of robotic surgery · 2026Review
- Equal and safe use of flexible bronchoscopy in intensive care units.ERJ open research · 2026Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Performance in flexible bronchoscopy varies even among experienced bronchoscopists. This study aimed to compare an autonomous bronchoscopy robot (BronchoBot) to human bronchoscopists in a standardised simulation-based setting. Methods: We compared 30 bronchoscopies performed by humans (10 novices, 10 intermediates and 10 experienced) to 10 bronchoscopies performed by BronchoBot on a realistic phantom. The primary outcomes were Anatomy Rating (0-12 points) and Dexterity Rating (0-6 points) assessed by two blinded expert raters. Secondary outcomes were Diagnostic Completeness (DC; 0-18 segments), Structured Progress (SP; 0-18 progressions), Procedure Time (PT; seconds) and Mean Intersegmental Time (MIT; seconds per segment), assessed by artificial intelligence (AI). Tertiary outcomes included five targeted navigations by BronchoBot to RB4→RB5→RB6 and LB8→LB9→LB10, following the bronchoscopy skills and task assessment tool (BSTAT), rated by AI. Results: BronchoBot significantly outperformed all three human groups for all outcome measures. Anatomy Rating (novice, intermediate, experienced Conclusions: BronchoBot outperformed experienced human bronchoscopists using validated assessment tools based on expert human and AI ratings. BronchoBot can serve a role as benchmarking expert performance in a simulated setting, but further development and evaluation are required for use in patients.
Identifiers
What 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.