ArticleDiagnostics (Basel, Switzerland)2024
Enhancing Lung Ultrasound Diagnostics: A Clinical Study on an Artificial Intelligence Tool for the Detection and Quantification of A-Lines and B-Lines.
Article in Diagnostics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The predictive value of newborn and infant lung ultrasound score for mechanical ventilation needs: a systematic review and meta-analysis.Frontiers in pediatrics · 2025Pooled it
- A modern radiologist's guide to artificial intelligence.Pediatric radiology · 2026Review
- Artificial Intelligence-Based Automated Analysis for Pleural Effusion Detection on Thoracic Ultrasound: A Systematic Review.Diagnostics (Basel, Switzerland) · 2026Review
- Automatic approach for B-lines detection in lung ultrasound images using You Only Look Once algorithm.Journal of ultrasound · 2025Observational
- Artificial Intelligence-Assisted Lung Ultrasound for Pneumothorax: Diagnostic Accuracy Compared with CT in Emergency and Critical Care.Tomography (Ann Arbor, Mich.) · 2025Article
- Improved A-Line and B-Line Detection in Lung Ultrasound Using Deep Learning with Boundary-Aware Dice Loss.Bioengineering (Basel, Switzerland) · 2025Article
- Performance of a point-of-care ultrasound platform for artificial intelligence-enabled assessment of pulmonary B-lines.Cardiovascular ultrasound · 2025Article
- Critical care ultrasound: development, evolution, current and evolving clinical concepts in critical care medicine.Frontiers in medicine · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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.