ArticleJournal of the American Society of Echocardiography : official publication of the American Society of Echocardiography2021
Use of Machine Learning to Improve Echocardiographic Image Interpretation Workflow: A Disruptive Paradigm Change?
Article in Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- Artificial intelligence-enhanced echocardiography in cardiovascular disease management.Nature reviews. Cardiology · 2026Review
- Automated analysis of echocardiographic images: do different artificial intelligence tools provide concordant measurements?The international journal of cardiovascular imaging · 2026Article
- The Growing Role of Intracardiac Echo in Congenital Heart Disease Interventions.Journal of clinical medicine · 2025Review
- AI in Echocardiography: State-of-the-art Automated Measurement Techniques and Clinical Applications.JMA journal · 2025Review
- Quantification of left ventricular mass in multiple views of echocardiograms using model-agnostic meta learning in a few-shot setting.PeerJ. Computer science · 2025Article
- Assessment of left ventricular wall thickness and dimension: accuracy of a deep learning model with prediction uncertainty.The international journal of cardiovascular imaging · 2024Article
- Machine Learning-Enabled Fully Automated Assessment of Left Ventricular Volume, Ejection Fraction and Strain: Experience in Pediatric and Young Adult Echocardiography.Pediatric cardiology · 2024Article
- Broadening Perspectives of Artificial Intelligence in Echocardiography.Cardiology and therapy · 2024Review
- Population data-based federated machine learning improves automated echocardiographic quantification of cardiac structure and function: theEuropean heart journal. Digital health · 2024Article
- Artificial Intelligence in the Screening, Diagnosis, and Management of Aortic Stenosis.Reviews in cardiovascular medicine · 2024Review
- Deep learning assisted measurement of echocardiographic left heart parameters: improvement in interobserver variability and workflow efficiency.The international journal of cardiovascular imaging · 2023Article
- An Automated View Classification Model for Pediatric Echocardiography Using Artificial Intelligence.Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography · 2022Article
- Artificial intelligence for the echocardiographic assessment of valvular heart disease.Heart (British Cardiac Society) · 2022Review
- Routine Echocardiography and Artificial Intelligence Solutions.Frontiers in cardiovascular medicine · 2021Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
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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.