Back to search

Article

Artificial intelligence-enabled echocardiography as a surrogate for multi-modality aortic stenosis imaging: post-hoc analysis of a clinical trial

2025-03-27

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Background</h4> Accurate aortic stenosis (AS) phenotyping requires access to multimodality imaging which has limited availability. The Digital Aortic Stenosis Severity Index (DASSi), an AI biomarker of AS-related remodeling on 2D echocardiography, predicts AS progression independent of Doppler measurements. Whether DASSi-enhanced echocardiography provides a scalable alternative to multimoda...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
a4f4188a-0668-5703-b8e5-08cd29949d06
DOI
10.1101/2025.03.26.25324690
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Artificial intelligence-enabled echocardiography as a surrogate for multi-modality aortic stenosis imaging: post-hoc analysis of a clinical trialDOI 10.1101/2025.03.26.25324690
Digital phenotyping of aortic stenosis-related remodeling reveals complementary structural, electrical, and hemodynamic signaturesSemantic proximity
Artificial Intelligence-Enhanced Comprehensive Assessment of the Aortic Valve Stenosis Continuum in EchocardiographySemantic proximity
Comprehensive aortic stenosis characterization using multi-view deep learningSemantic proximity
A Machine-Learning Framework to Identify Distinct Phenotypes of Aortic Stenosis Severity.Semantic proximity
Phenotypic Selectivity of Artificial Intelligence-enhanced Electrocardiography in Cardiovascular Diagnosis and Risk PredictionSemantic proximity
Echocardiography-Based, Artificial Intelligence-Enabled Electrocardiography (AI-ECG) for Diastolic Hemodynamics Phenotyping in Acute Heart Failure (AHF)Semantic proximity
Multiethnic Validation of Artificial Intelligence-Enhanced Electrocardiographic Image Analysis in Detecting Cardiac Structural and Functional Abnormalities: A UK Biobank StudySemantic proximity
Artificial intelligence in medical imaging: A radiomic guide to precision phenotyping of cardiovascular disease.Semantic proximity
The Future of Imaging in Heart Failure: Toward Precision Phenotyping, Integration, and Intelligence.Semantic proximity
Composite Artificial Intelligence–Enabled Electrocardiogram for Detection and Prediction of Structural Heart DiseaseSemantic proximity
Multi-task artificial intelligence annotation of echocardiographic images: a retrospective multi-cohort studySemantic proximity
Automated Phenotyping of Mitral Stenosis Using Deep LearningSemantic proximity
Select a neighboring publication to make it the new centre.