ReviewTherapeutic advances in pulmonary and critical care medicine
Artificial Intelligence in Interventional Pulmonology.
Review in Therapeutic advances in pulmonary and critical care medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Artificial Intelligence-Induced Deskilling in Interventional Pulmonology: An International Cross-Sectional Survey on Risk Perception and Mitigation Strategies.Advances in respiratory medicine · 2026Observational
- Artificial Intelligence in Pulmonary Endoscopy: Current Evidence, Limitations, and Future Directions.Journal of imaging · 2026Review
- Decoding the "black-box": explainable artificial intelligence towards trustworthy advancement in respiratory medicine.Breathe (Sheffield, England) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is an exciting new technology poised to drastically improve the practice of medicine. Interventional pulmonology (IP) is particularly well situated to implement AI due to the variety of complex diagnostic and therapeutic techniques within its scope. By integrating AI into the field, the procedure planning and management of pulmonary disease should become easier, more accessible, and more effective. AI has already been implemented in the diagnostic techniques of navigational and virtual bronchoscopy, endobronchial ultrasound, and for the rapid onsite evaluation of pathological specimens. The goal of this review is to summarize recent utilization of AI in IP and to discuss the origins of the technology, ethical considerations, and future directions.
Indexed as
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.