Article

Deep learning enhanced magnetocardiography enables multi-task detection of coronary, ventricular, and rhythm disorders

2025-12-02

Abstract excerpt

<h4>Background</h4> Magnetocardiography (MCG) captures the magnetic fields generated by myocardial currents, theoretically preserving electrophysiological details lost in surface potentials. However, its clinical application has been hindered by small datasets and the complexity of analysing high-dimensional magnetic field data. We sought to develop a self-supervised deep learning framework to detect high burden...

Topics

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

Identifiers and source

Literature Corpus work: 1d9eeb7c-5d75-5f90-a31f-6daf03bd538b
DOI: 10.64898/2025.11.30.25341301

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Deep learning enhanced magnetocardiography enables multi-task detection of coronary, ventricular, and rhythm disordersDOI 10.64898/2025.11.30.25341301Read

Clinically Aligned Explainable AI Improves Myocardial Infarction Detection Using Multi-Lead ElectrocardiographySemantic proximity Read

Deep learning enables diagnosis of atrial cardiomyopathy from routine 12-lead electrocardiogramSemantic proximity Read

Automated Multilabel Diagnosis on Electrocardiographic Images and SignalsSemantic proximity Read

Deep representation learning of electrocardiogram reveals novel insights in cardiac structure and functions and connections to cardiovascular diseasesSemantic proximity Read

Electrocardiogram-Based Deep Learning for Time-Resolved Prediction of Heart Failure With Reduced Ejection Fraction: A Multinational StudySemantic proximity Read

CARDIAC-FM: A Multimodal Foundation Model for Cardiovascular Risk Prediction Using ECG and Cardiac MRISemantic proximity Read

A Fast, Lightweight, and Generalizable Deep Neural Network for the Detection of Atrial FibrillationSemantic proximity Read

An Ensemble Deep Learning Algorithm for Structural Heart Disease Screening Using Electrocardiographic Images: PRESENT SHDSemantic proximity Read

Biometric Contrastive Learning for Data-Efficient Deep Learning from Electrocardiographic ImagesSemantic proximity Read

Deep Learning Approaches for Electrocardiogram (ECG) Analysis: Challenges and ApplicationsSemantic proximity Read

Automated Heart Disease Detection Using Swin Transformer and ECG Signal Processing: A High-Accuracy ApproachSemantic proximity Read

A self-supervised electrocardiogram foundation model for empowering cardiovascular disease prediction and genetic factor discovery.Semantic proximity Read