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Peer-Reviewed Publication
NPJ Cardiovasc Health2026;3(1)April 1, 2026Journal Article

A view-flexible deep learning framework for automated analysis of 2D echocardiography.

D M Anisuzzaman1, Jeffrey G Malins1, John I Jackson1, Eunjung Lee1, Jwan A Naser1, Behrouz Rostami1, Jared G Bird1, Dan Spiegelstein2, Talia Amar2, Christie C Ngo1, Jae K Oh1, Patricia A Pellikka1, Jeremy J Thaden1, Francisco Lopez-Jimenez1, Timothy J Poterucha1, Paul A Friedman1, Sorin V Pislaru1, Garvan C Kane1, Zachi I Attia3
1Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, US.
2UltraSight Ltd., Rehovot, Israel.
3Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, US. attia.itzhak@mayo.edu.
PubMed PMC DOI PDF

Abstract

Echocardiography traditionally requires experienced operators to select and interpret clips from specific viewing angles. Clinical decision-making is therefore limited for handheld cardiac ultrasound (HCU), which is often collected by novice users. In this study, we developed a view-flexible deep learning framework to estimate left ventricular ejection fraction (LVEF), patient age, and patient sex…

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