ReviewPediatric radiology2022
Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective.
Review in Pediatric radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled 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.
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
30 citing papers in PubMed, 1 synthesis or guideline pooled it.
- State-of-the-art review of lung imaging in cystic fibrosis with recommendations for pulmonologists and radiologists from the "iMAging managEment of cySTic fibROsis" (MAESTRO) consortium.European respiratory review : an official journal of the European Respiratory Society · 2022Pooled it
- Artificial Intelligence in Pediatric Imaging: A Primer for Pediatric Clinicians.Indian journal of pediatrics · 2026Review
- Artificial intelligence and pediatric imaging data: ethical strategies for learning and collaboration.Pediatric radiology · 2026Review
- Imaging and characterization of pulmonary nodules in children with solid tumors: what makes a pulmonary nodule a metastasis?Pediatric radiology · 2026Review
- Pediatric-specific computer-aided detection of lung nodules in computed tomography scans.Journal of medical imaging (Bellingham, Wash.) · 2026Article
- Artificial intelligence in pediatrics: a bibliometric analysis of global output, networks, and frontiers [2016-2025].Translational pediatrics · 2026Article
- Innovations in pediatric imaging: a scoping review of the past decade with case illustrations.World journal of pediatrics : WJP · 2026Article
- Diagnostic Performance of ChatGPT-5 for Detecting Pediatric Pneumothorax on Chest Radiographs: A Multi-Prompt Evaluation.Diagnostics (Basel, Switzerland) · 2026Article
- Radiomics and Artificial Intelligence in Pulmonary Fibrosis.Journal of imaging informatics in medicine · 2025Review
- Evaluation of an artificial intelligence noise reduction tool for conventional X-ray imaging - a visual grading study of pediatric chest examinations at different radiation dose levels using anthropomorphic phantoms.Pediatric radiology · 2025Article
- Pulmonary MRI in Newborns and Children.Journal of magnetic resonance imaging : JMRI · 2025Review
- A Thorough Review of the Clinical Applications of Artificial Intelligence in Lung Cancer.Cancers · 2025Review
- Multilevel support-assisted prototype optimization network for few-shot medical segmentation of lung lesions.Scientific reports · 2025Article
- The unintended consequences of artificial intelligence in paediatric radiology.Pediatric radiology · 2024Article
- Revolutionising paediatric radiology: the future impact of artificial intelligence.European radiology · 2024Article
- The Role of AI in Hospitals and Clinics: Transforming Healthcare in the 21st Century.Bioengineering (Basel, Switzerland) · 2024Review
- Doctor's Orders-Why Radiologists Should Consider Adjusting Commercial Machine Learning Applications in Chest Radiography to Fit Their Specific Needs.Healthcare (Basel, Switzerland) · 2024Article
- Paediatric Thoracic Imaging in Cystic Fibrosis in the Era of Cystic Fibrosis Transmembrane Conductance Regulator Modulation.Children (Basel, Switzerland) · 2024Review
- DraiNet: AI-driven decision support in pneumothorax and pleural effusion management.Pediatric surgery international · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) applications for chest radiography and chest CT are among the most developed applications in radiology. More than 40 certified AI products are available for chest radiography or chest CT. These AI products cover a wide range of abnormalities, including pneumonia, pneumothorax and lung cancer. Most applications are aimed at detecting disease, complemented by products that characterize or quantify tissue. At present, none of the thoracic AI products is specifically designed for the pediatric population. However, some products developed to detect tuberculosis in adults are also applicable to children. Software is under development to detect early changes of cystic fibrosis on chest CT, which could be an interesting application for pediatric radiology. In this review, we give an overview of current AI products in thoracic radiology and cover recent literature about AI in chest radiography, with a focus on pediatric radiology. We also discuss possible pediatric applications.
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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.