SynthesisEuropean respiratory review : an official journal of the European Respiratory Society2025
Artificial intelligence in bronchoscopy: a systematic review.
Synthesis in European respiratory review : an official journal of the European Respiratory Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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
11 citing papers in PubMed.
- Artificial intelligence-based image recognition in bronchoscopy: software development and randomized controlled trial for training evaluation in intensive care residents.BMC medical education · 2026Trial
- Artificial Intelligence-Induced Deskilling in Interventional Pulmonology: An International Cross-Sectional Survey on Risk Perception and Mitigation Strategies.Advances in respiratory medicine · 2026Observational
- Recent advances in artificial intelligence across interventional pulmonology: a narrative review.Journal of thoracic disease · 2026Review
- Applications of Artificial Intelligence in Endobronchial Ultrasound for Lung Cancer Diagnosis and Staging: A Scoping Review.Current oncology (Toronto, Ont.) · 2026Article
- Artificial Intelligence in Pediatric Bronchoscopy: Current Evidence and Future Perspectives.Pediatric pulmonology · 2026Review
- Review
- An autonomous bronchoscopy robot controlled by artificial intelligence (BronchoBot) outperforms experienced bronchoscopists in a simulated setting.ERJ open research · 2026Article
- Multi-adapter SAM-inspired bronchoscopic image segmentation for lung cancer diagnosis.Frontiers in oncology · 2026Article
- Artificial intelligence-assisted rapid on-site evaluation in liver biopsy: a diagnostic accuracy study.Frontiers in oncology · 2026Article
- Artificial intelligence for rapid on-site evaluation of lymph node fine-needle aspiration: improving diagnostic efficiency and accuracy.Frontiers in medicine · 2026Article
- Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial intelligence (AI) systems have been implemented to improve the diagnostic yield and operators' skills within endoscopy. Similar AI systems are now emerging in bronchoscopy. Our objective was to identify and describe AI systems in bronchoscopy.
methodsA systematic review was performed using MEDLINE, Embase and Scopus databases, focusing on two terms: bronchoscopy and AI. All studies had to evaluate their AI against human ratings. The methodological quality of each study was assessed using the Medical Education Research Study Quality Instrument (MERSQI).
results1196 studies were identified, with 20 passing the eligibility criteria. The studies could be divided into three categories: nine studies in airway anatomy and navigation, seven studies in computer-aided detection and classification of nodules in endobronchial ultrasound, and four studies in rapid on-site evaluation. 16 were assessment studies, with 12 showing equal performance and four showing superior performance of AI compared with human ratings. Four studies within airway anatomy implemented their AI, all favouring AI guidance to no AI guidance. The methodological quality of the studies was moderate (mean MERSQI 12.9 points, out of a maximum 18 points).
interpretation20 studies developed AI systems, with only four examining the implementation of their AI. The four studies were all within airway navigation and favoured AI to no AI in a simulated setting. Future implementation studies are warranted to test for the clinical effect of AI systems within bronchoscopy.
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