Prediction of heart failure risk factors from retinal optical imaging via explainable machine learning

Prediction of heart failure risk factors from retinal optical imaging via explainable machine learning

Over 64 million people worldwide are affected by heart failure (HF), a condition that significantly raises mortality and medical expenses. In this study, we explore the potential of retinal optical coherence tomography (OCT) features as non-invasive biomarkers for the classification of heart failure...

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Bibliographic Details
Main Authors: Sona M. Al Younis, Samit Kumar Ghosh, Hina Raja, Feryal A. Alskafi, Siamak Yousefi, Ahsan H. Khandoker
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-03-01
Series:Frontiers in Medicine
Subjects:
cardiovascular diseases
heart failure
machine learning
deep learning
explainable AI
UK Biobank
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2025.1551557/full
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