ArticleJournal of the American Heart Association2024
Quantitative Prediction of Right Ventricular Size and Function From the ECG.
Article in Journal of the American Heart Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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.
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Who cites it
12 citing papers in PubMed, 13 citations in OpenAlex.
- Automated assessment of right heart function by artificial intelligence: A systematic review and meta-analysis.European journal of radiology open · 2026Article
- Artificial Intelligence-Enhanced Electrocardiogram for Longitudinal Evaluation of Right Ventricular Dysfunction After Acute Pulmonary Embolism: Rational and Design of CURES-CARE Study.Pulmonary circulation · 2026Article
- Automated assessment of right ventricular systolic function from coronary angiograms with video-based artificial intelligence algorithms: development, validation, comparison against humans, and prospective deployment.European heart journal. Digital health · 2026Article
- Electrocardiographic changes in immune checkpoint inhibitor-associated cardiac injury: a narrative review.Cardiovascular diagnosis and therapy · 2026Review
- Development and multicentre validation of an artificial intelligence electrocardiogram model for ventricular remodeling in repaired tetralogy of Fallot.European heart journal. Digital health · 2026Article
- A foundation transformer model with self-supervised learning for ECG-based assessment of cardiac and coronary function.NEJM AI · 2025Article
- Consequences of Right Heart Disease for Cardiac Electrophysiology and Arrhythmias: Cellular and Structural Mechanisms.CJC open · 2025Review
- Anatomical-electrical coupling of cardiac axes: Definitions and population variability for advancing personalised ECG interpretation.PLoS computational biology · 2025Article
- Machine learning prediction of right ventricular volume and ejection fraction from two-dimensional echocardiography in patients with pulmonary regurgitation.The international journal of cardiovascular imaging · 2025Article
- Artificial intelligence-enhanced patient evaluation: bridging art and science.European heart journal · 2024Review
- Ensemble Modeling of Multimodal Electrocardiogram and Echocardiogram Data Improves Quantitative Assessment of Right Ventricular Function.JACC. Advances · 2024Article
- Deep Learning-Based Electrocardiogram Analysis Predicts Biventricular Dysfunction and Dilation in Congenital Heart Disease.Journal of the American College of Cardiology · 2024Article
Corrections and comments
- Update of
Authors and funding
14 authors at 5 institutions in 1 country.
Funding
Abstract
backgroundRight ventricular ejection fraction (RVEF) and end-diastolic volume (RVEDV) are not readily assessed through traditional modalities. Deep learning-enabled ECG analysis for estimation of right ventricular (RV) size or function is unexplored. METHODS AND
resultsWe trained a deep learning-ECG model to predict RV dilation (RVEDV >120 mL/m
conclusionsDeep learning-ECG analysis can identify significant cardiac magnetic resonance imaging RV dysfunction and dilation with good performance. Predicted RVEF is associated with clinical outcome.
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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.