Peer-Reviewed Publication
Eur Heart J Digit Health2026;7(8):ztag140.October 1, 2026Journal Article

Point-of-care echocardiography screening for hypertrophic cardiomyopathy using automated deep-learning analysis.

Nour Karra1,2, Yarin Klempfner3, Viana Copeland1, Michael Fiman3, Harel Doitch3, Roei Merin2,4, Robert Klempfner1,3, Ehud Schwammenthal2,3, Michael Arad1,2, Elad Maor1,2,3
1Leviev Heart and Vascular Center, Chaim Sheba Medical Center, Derech Sheba 2, Tel Hashomer, 52621 Ramat Gan, Israel.
2The Gray Faculty of Medical & Health Sciences, Tel Aviv University, Ramat Aviv, 69978 Tel Aviv, Israel.
3AISAP.ai, Derech Sheba 2, 5266202 Ramat Gan, Israel.
4Tel Aviv Sourasky Medical Center, Affiliated to the Gray Faculty of Medical & Health Sciences, Tel Aviv University, Israel.

Abstract

AIMS: Hypertrophic cardiomyopathy (HCM) remains underdiagnosed due to limited access to expert imaging. We developed and validated a deep-learning (DL)-based echocardiographic model adaptable to point-of-care ultrasound (POCUS) for scalable HCM screening. METHODS AND RESULTS: We retrospectively analysed 134 956 expert transthoracic echocardiograms (TTE) from 73 598 patients at Sheba Medical Cente…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.