MAR-GCNet: Multi-label abnormal detection of electrocardiograms by combining multiscale features and graph convolutional networks

No abstract is available for this paper.

• Publication year

  2026

• Venue

  Biomedical Signal Processing and Control

• Publication date

  Unknown publication date

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1016/j.bspc.2026.109841
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Large Language Model-assisted multi-scale hierarchical classification of ECG signals

  2025cited by this paper
• Dual-branch fusion network with mutual learning for 12-lead electrocardiogram signal classification

  2025cited by this paper
• A dual-branch convolutional neural network with domain-informed attention for arrhythmia classification of 12-lead electrocardiograms

  2025cited by this paper
• Enhancing automatic multilabel diagnosis of electrocardiogram signals: A masked transformer approach

  2025cited by this paper
• Application of Tswin-F network based on multi-scale feature fusion in tomato leaf lesion recognition

  2024cited by this paper
• Artificial Intelligence Interpretation of the Electrocardiogram: A State-of-the-Art Review

  2024cited by this paper
• ECG-based data-driven solutions for diagnosis and prognosis of cardiovascular diseases: A systematic review

  2024cited by this paper
• Multi-Scale and Multi-Channel Information Fusion for Exercise Electrocardiogram Feature Extraction and Classification

  2024cited by this paper
• 12-Lead ECG signal classification for detecting ECG arrhythmia via an information bottleneck-based multi-scale network

  2024cited by this paper
• Conv-RGNN: An efficient Convolutional Residual Graph Neural Network for ECG classification

  2024cited by this paper
• Deep Learning Applications in ECG Analysis and Disease Detection: An Investigation Study of Recent Advances

  2024cited by this paper
• ECG signal feature extraction trends in methods and applications

  2023cited by this paper
• A Multi-View Multi-Scale Neural Network for Multi-Label ECG Classification

  2023cited by this paper
• ECG Based Heart Disease Classification: Advancement and Review of Techniques

  2023cited by this paper
• ST-ReGE: A Novel Spatial-Temporal Residual Graph Convolutional Network for CVD

  2023cited by this paper
• A Multi-Scale Convolution and Multi-Layer Fusion Network for Remote Sensing Forest Tree Species Recognition

  2023cited by this paper
• A token selection-based multi-scale dual-branch CNN-transformer network for 12-lead ECG signal classification

  2023cited by this paper
• A Review of the F-Measure: Its History, Properties, Criticism, and Alternatives

  2023cited by this paper
• Towards Understanding Generalization of Macro-AUC in Multi-label Learning

  2023cited by this paper
• Deep Learning-Based ECG Arrhythmia Classification: A Systematic Review

  2023cited by this paper
• An Attentive Spatio-Temporal Learning-Based Network for Cardiovascular Disease Diagnosis

  2023cited by this paper
• Automatic diagnosis and localization of myocardial infarction using morphological features of ECG signal

  2023cited by this paper
• Age, sex and race bias in automated arrhythmia detectors.

  2022cited by this paper
• Detecting ECG abnormalities using an ensemble framework enhanced by Bayesian belief network

  2022cited by this paper
• Detection of cardiac arrhythmias from ECG signals using FBSE and Jaya optimized ensemble random subspace K-nearest neighbor algorithm

  2022cited by this paper
• The Use of Wearable ECG Devices in the Clinical Setting: a Review

  2022cited by this paper
• Arrhythmia Disease Diagnosis Based on ECG Time–Frequency Domain Fusion and Convolutional Neural Network

  2022cited by this paper
• Atrial Conduction Disorders

  2021cited by this paper
• ECG signal classification based on deep CNN and BiLSTM

  2021cited by this paper
• Machine Learning-Based Heart Disease Diagnosis: A Systematic Literature Review

  2021cited by this paper
• Classification of ECG beats using optimized decision tree and adaptive boosted optimized decision tree

  2021cited by this paper
• Classification of electrocardiogram signals with waveform morphological analysis and support vector machines

  2021cited by this paper
• Deep learning in ECG diagnosis: A review

  2021cited by this paper
• Artificial intelligence-enhanced electrocardiography in cardiovascular disease management

  2021cited by this paper
• Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL

  2020cited by this paper
• MLBF-Net: A Multi-Lead-Branch Fusion Network for Multi-Class Arrhythmia Classification Using 12-Lead ECG

  2020cited by this paper
• PTB-XL, a large publicly available electrocardiography dataset

  2020cited by this paper
• A novel method for ECG signal classification via one-dimensional convolutional neural network

  2020cited by this paper
• Detection and Classification of Cardiac Arrhythmias by a Challenge-Best Deep Learning Neural Network Model

  2019cited by this paper
• InceptionTime: Finding AlexNet for time series classification

  2019cited by this paper
• Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network

  2019cited by this paper
• Graph Convolutional Networks for Text Classification

  2018cited by this paper
• LSTM-Based ECG Classification for Continuous Monitoring on Personal Wearable Devices

  2018cited by this paper
• Correlation analysis of performance measures for multi-label classification

  2018cited by this paper
• Automated detection of arrhythmias using different intervals of tachycardia ECG segments with convolutional neural network

  2017cited by this paper
• Adam: A Method for Stochastic Optimization

  2014cited by this paper
• Using standardized numerical scores for the display and interpretation of biomedical data.

  2011cited by this paper
• Competency in Interpretation of 12-Lead Electrocardiograms: A Summary and Appraisal of Published Evidence

  2003cited by this paper
• The impact of the MIT-BIH Arrhythmia Database

  2001cited by this paper
• The European ST-T database: standard for evaluating systems for the analysis of ST-T changes in ambulatory electrocardiography.

  1992cited by this paper

• No citing papers are available for this paper.