AIMC Topic: Ventricular Function, Right

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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 Mar 13, 2025
Right ventricular (RV) end-diastolic volume (RVEDV) and ejection fraction (RVEF) by cardiac MRI (cMRI) guide management in chronic pulmonary regurgitation (PR). Two-dimensional echocardiography suboptimally correlate with RV volumes. This study teste...
Reproducibility of Results Young Adult Adult Male Stroke Volume Machine Learning Prognosis Retrospective Studies Humans Female Predictive Value of Tests Ventricular Dysfunction, Right Image Interpretation, Computer-Assisted Ventricular Function, Right Echocardiography Pulmonary Valve Insufficiency Severity of Illness Index Adolescent Chronic Disease
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Deep Learning-Enabled Assessment of Right Ventricular Function Improves Prognostication After Transcatheter Edge-to-Edge Repair for Mitral Regurgitation.

Circulation. Cardiovascular imaging Jan 21, 2025
BACKGROUND: Right ventricular (RV) function has a well-established prognostic role in patients with severe mitral regurgitation (MR) undergoing transcatheter edge-to-edge repair (TEER) and is typically assessed using echocardiography-measured tricusp...
Severity of Illness Index Deep Learning Predictive Value of Tests Registries Aged, 80 and over Cardiac Catheterization Male Humans Ventricular Function, Right Mitral Valve Stroke Volume Prognosis Mitral Valve Insufficiency Echocardiography Female Aged
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Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence-Enabled ECGs.

Journal of the American Heart Association Nov 4, 2024
BACKGROUND: Early detection of left and right ventricular systolic dysfunction (LVSD and RVSD respectively) in children can lead to intervention to reduce morbidity and death. Existing artificial intelligence algorithms can identify LVSD and RVSD in ...
Male Ventricular Function, Left Stroke Volume Echocardiography Artificial Intelligence Algorithms Retrospective Studies Female Electrocardiography Predictive Value of Tests Ventricular Dysfunction, Right Ventricular Dysfunction, Left Ventricular Function, Right Infant Adolescent Child, Preschool Child Humans
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Automated biventricular quantification in patients with repaired tetralogy of Fallot using a three-dimensional deep learning segmentation model.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Sep 11, 2024
BACKGROUND: Deep learning is the state-of-the-art approach for automated segmentation of the left ventricle (LV) and right ventricle (RV) in cardiovascular magnetic resonance (CMR) images. However, these models have been mostly trained and validated ...
Humans Female Reproducibility of Results Young Adult Databases, Factual Adolescent Imaging, Three-Dimensional Ventricular Function, Right Adult Child Retrospective Studies Treatment Outcome Male Predictive Value of Tests Tetralogy of Fallot Ventricular Function, Left Magnetic Resonance Imaging, Cine Deep Learning Cardiac Surgical Procedures Heart Ventricles Image Interpretation, Computer-Assisted Automation
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Clinical utility of a rapid two-dimensional balanced steady-state free precession sequence with deep learning reconstruction.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Jul 28, 2024
BACKGROUND: Cardiovascular magnetic resonance (CMR) cine imaging is still limited by long acquisition times. This study evaluated the clinical utility of an accelerated two-dimensional (2D) cine sequence with deep learning reconstruction (Sonic DL) t...
Deep Learning Time Factors Predictive Value of Tests Heart Ventricles Magnetic Resonance Imaging, Cine Ventricular Function, Right Image Interpretation, Computer-Assisted Observer Variation Male Humans Ventricular Function, Left Prospective Studies Stroke Volume Middle Aged Female Reproducibility of Results Aged Adult
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Towards deep learning methods for quantification of the right ventricle using 2D echocardiography.

Future cardiology Jun 10, 2024
Ventricular Dysfunction, Right Heart Ventricles Ventricular Function, Right Humans Echocardiography Deep Learning
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An attention-based deep learning method for right ventricular quantification using 2D echocardiography: Feasibility and accuracy.

Echocardiography (Mount Kisco, N.Y.) Dec 21, 2023
AIM: To test the feasibility and accuracy of a new attention-based deep learning (DL) method for right ventricular (RV) quantification using 2D echocardiography (2DE) with cardiac magnetic resonance imaging (CMR) as reference.
Ventricular Function, Right Middle Aged Deep Learning Feasibility Studies Ventricular Dysfunction, Right Reproducibility of Results Humans Male Adult Retrospective Studies Stroke Volume Female Echocardiography
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Deep Learning-Based Prediction of Right Ventricular Ejection Fraction Using 2D Echocardiograms.

JACC. Cardiovascular imaging May 10, 2023
BACKGROUND: Evidence has shown the independent prognostic value of right ventricular (RV) function, even in patients with left-sided heart disease. The most widely used imaging technique to measure RV function is echocardiography; however, convention...
Echocardiography Deep Learning Predictive Value of Tests Ventricular Dysfunction, Right Humans Retrospective Studies Stroke Volume Ventricular Function, Right
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Natural language processing for identification of hypertrophic cardiomyopathy patients from cardiac magnetic resonance reports.

BMC medical informatics and decision making Oct 18, 2022
BACKGROUND: Cardiac magnetic resonance (CMR) imaging is important for diagnosis and risk stratification of hypertrophic cardiomyopathy (HCM) patients. However, collection of information from large numbers of CMR reports by manual review is time-consu...
Ventricular Function, Right Humans Natural Language Processing Stroke Volume Cardiomyopathy, Hypertrophic Artificial Intelligence Magnetic Resonance Imaging Magnetic Resonance Spectroscopy
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Assessment of right ventricular size and function from cardiovascular magnetic resonance images using artificial intelligence.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Apr 11, 2022
BACKGROUND: Theoretically, artificial intelligence can provide an accurate automatic solution to measure right ventricular (RV) ejection fraction (RVEF) from cardiovascular magnetic resonance (CMR) images, despite the complex RV geometry. However, in...
Magnetic Resonance Imaging, Cine Ventricular Function, Right Magnetic Resonance Imaging Humans Predictive Value of Tests Artificial Intelligence Ventricular Dysfunction, Right Reproducibility of Results Heart Ventricles Stroke Volume
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