Back to search

Article

Automated Aortic Regurgitation Detection and Quantification: A Deep Learning Approach Using Multi-View Echocardiography

2025-03-19

Abstract excerpt

<h4>Background</h4> Accurate evaluation of aortic regurgitation (AR) severity is necessary for early detection and chronic disease management. AR is most commonly assessed by Doppler echocardiography, however limitations remain given variable image quality and need to integrate information from multiple views. This study developed and validated a deep learning model for automated AR severity assessment from multi-...

Topics

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

Identifiers and source

Literature Corpus work
ba9cb167-7cfe-564a-b647-792f1b530c9c
DOI
10.1101/2025.03.18.25323918
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.
Automated Aortic Regurgitation Detection and Quantification: A Deep Learning Approach Using Multi-View EchocardiographyDOI 10.1101/2025.03.18.25323918
Select a neighboring publication to make it the new centre.