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Systematic Bronchoscopy: the Four Landmarks Approach
Published on: June 23, 2023
Artificial Intelligence in Pediatric Bronchoscopy: Current Evidence and Future Perspectives
Patrick Stafler1,2, Saharon Less Elazari1,2
1Pulmonary Institute, Schneider Children's Medical Center of Israel, Petach Tikva, Israel.
Pediatric Pulmonology
|May 18, 2026
Summary
Artificial intelligence (AI) shows promise in pediatric bronchoscopy for improving diagnostics and training. Further research with multi-center pediatric data is needed to overcome current limitations and integrate AI effectively.
Area of Science:
- Medical technology and artificial intelligence
- Pediatric respiratory medicine
Background:
- Artificial intelligence (AI) is advancing medical endoscopy, with established benefits in adult bronchoscopy.
- Pediatric bronchoscopy presents unique challenges, and AI integration is an emerging area of research.
Purpose of the Study:
- To review current evidence on artificial intelligence applications in pediatric bronchoscopy.
- To explore potential future uses of AI in pediatric airway procedures.
Main Methods:
- Systematic literature search of PubMed and EMBASE for AI in pediatric bronchoscopy.
- Inclusion of relevant adult bronchoscopy studies where pediatric data were limited.
- Focus on AI for video analysis, navigation, diagnostics, and training, noting data challenges.
Main Results:
- Deep learning models achieve expert-level accuracy in identifying airway anatomy from bronchoscopy video.
- AI in simulators enhances novice training in completeness, structure, and speed.
- AI analysis of radiographs shows high accuracy for foreign body aspiration, potentially reducing bronchoscopies.
Conclusions:
- AI in pediatric bronchoscopy is nascent, with current evidence largely based on adult practice.
- AI holds potential to enhance diagnostic accuracy, patient safety, and training efficiency.
- Advancement requires collaborative, multi-center pediatric data, prospective trials, and workflow integration.
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Description
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