A robust and data-efficient deep learning model for cardiac assessment without segmentation

Authors

Ricardo Henao (ORCID: https://orcid.org/0000-0003-4980-845X)
Conor M. Artman

Institutions

Lawrence Livermore National Laboratory (US)
Duke University (US)

Publication Details

Journal: BMC Medical Imaging
Published: 2025-10-22
DOI: https://doi.org/10.1186/s12880-025-01903-x
Primary Topic: ECG Monitoring and Analysis
Type: article
Field-Weighted Citation Impact: 0.00

Funders

National Heart, Lung, and Blood Institute

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article

A robust and data-efficient deep learning model for cardiac assessment without segmentation

Ricardo Henao, Conor M. Artman

Oct 22, 2025

BMC Medical Imaging

ECG Monitoring and Analysis

article

A robust and data-efficient deep learning model for cardiac assessment without segmentation

Ricardo Henao, Conor M. Artman

October 22, 2025article en

Abstract

No abstract available for this paper.

BMC Medical ImagingVol. 25(1)

Lawrence Livermore National Laboratory (US), Duke University (US)

National Heart, Lung, and Blood Institute

Openalex Percentile: Top 55%

ECG Monitoring and Analysis

DOI Open Access PDF OpenAlex

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A robust and data-efficient deep learning model for cardiac assessment without segmentation — Ricardo Henao, Conor M. Artman · BMC Medical Imaging (2025) | TGRS Research Map | TGRS