Article

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

2025-08-20

Abstract excerpt

<title>Abstract</title> <p>Cardiovascular diseases (CVDs) are a leading cause of global mortality, necessitating early and accurate detection for improved patient outcomes. Electrocardiography (ECG) is a fundamental diagnostic tool for identifying cardiac abnormalities; however, traditional methods rely on manual interpretation and conventional machine learning (ML) models, which often struggle with feature extra...

Topics

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

Identifiers and source

Literature Corpus work: 01acd55d-c760-5f9f-af42-971ea6b8e1b5
DOI: 10.21203/rs.3.rs-7198800/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Automated Heart Disease Detection Using Swin Transformer and ECG Signal Processing: A High-Accuracy ApproachDOI 10.21203/rs.3.rs-7198800/v1Read

A foundation transformer model with self-supervised learning for ECG-based assessment of cardiac and coronary functionSemantic proximity Read

Machine Learning, Deep Learning, and Hybrid Approaches for ECG-Based Cardiac Arrhythmia Detection: Techniques, Challenges, and Future PerspectivesSemantic proximity Read

AI-Enhanced ECG Intelligence: Optimized Deep Learning Pipelines for Early and Reliable Detection of Cardiac DisordersSemantic proximity Read

A Hybrid Model Combining 1D-CNN and BERT for Intelligent ECG Arrhythmia ClassificationSemantic proximity Read

Prospective Validation of a Deep Learning Model to Detect Structural Heart Disease from Apple Watch ECGs: The WATCH-SHD StudySemantic proximity Read

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

CTRhythm: Accurate Atrial Fibrillation Detection from Single-Lead ECG by Convolutional Neural Network and Transformer IntegrationSemantic proximity Read

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

Ensemble Post-hoc Explainable AI for Multilead ECG: Identifying Disease-Relevant Features in Single-Lead InterpretationsSemantic 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

A Coordinated Adaptive Multiscale Enhanced Spatio-Temporal Fusion Network for Multi-lead Electrocardiogram Arrhythmia DetectionSemantic proximity Read