Electrocardiogram Classification

Also known as ECG

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Overview

Electrocardiogram classification maps ECG signals to rhythm labels or cardiac diagnoses, from beat-level arrhythmias to multi-label screening for structural disease. Methods include convolutional and recurrent networks, Transformers and state-space models, engineered morphology and heart-rate features, and self-supervised foundation models often adapted with ECG reports or other clinical data. Models are evaluated on benchmarks such as PTB-XL and MIT-BIH, with growing attention to patient-held-out and cross-site tests, reduced-lead recordings, and wearable settings. A central challenge is whether strong benchmark results generalize across patients and devices, especially for rare or ambiguous labels, while remaining calibrated, interpretable, and efficient enough for clinical use.

Latest papers

CardsList

108 papers9 papers in the last four weeks, down 25% on the four weeks before. 0.1% of all new papers.

  1. Holter-to-Sleep: AI-Enabled Repurposing of Single-Lead ECG for Sleep Phenotyping

    Mar 19, 2026Donglin Xie, Qingshuo Zhao, Jingyu Wang +9Wearable Health MonitoringElectrocardiography

    National Institute of Health Data Science, Peking University, Beijing, China · Institute of Medical Technology, Peking University Health Science Center, Beijing, China · Department of Computer Science, Tianjin University of Technology, Tianjin, China +6

  2. Stress Classification from ECG Signals Using Vision Transformer

    Mar 19, 2026Zeeshan Ahmad, Naimul KhanElectrocardiogram ClassificationElectrocardiography

  3. Interpretable Classification of Time Series Using Euler Characteristic Surfaces

    Mar 16, 2026Salam Rabindrajit Luwang, Sushovan Majhi, Vishal Mandal +3Interpretable Time-Series ClassificationTime Series Classification

    National Institute of Technology, Department of Physics, Ravangla, 737139, India · George Washington University, Data science program, Washington, DC, 20052, USA · Montana Technological University, Department of Mathematical Sciences, Butte, 59701, USA

  4. Artificial intelligence-enabled single-lead ECG for non-invasive hyperkalemia detection: development, multicenter validation, and proof-of-concept deployment

    Mar 15, 2026Gongzheng Tang, Qinghao Zhao, Guangkun Nie +10Electrocardiogram Classification

    Institute of Medical Technology, Peking University Health Science Center, Beijing, China · National Institute of Health Data Science, Peking University, Beijing, China · Department of Cardiology, Peking University People’s Hospital, Beijing, China +8

  5. Echo2ECG: Enhancing ECG Representations with Cardiac Morphology from Multi-View Echos

    Mar 9, 2026Michelle Espranita Liman, Özgün Turgut, Alexander Müller +3Electrocardiogram Representation LearningMultimodal Learning

    Chair for AI in Healthcare and Medicine, Technical University of Munich (TUM) and TUM University Hospital, Germany · Department of Cardiology, TUM University Hospital, Germany · Department of Computing, Imperial College London, UK +1

  6. Electrocardiogram Classification with Transformers Using Koopman and Wavelet Features

    Mar 9, 2026Sucheta Ghosh, Zahra MonfaredElectrocardiogram ClassificationTime Series Transformers

    Interdisciplinary Center for Scientific Computing, Heidelberg University, Germany · Department of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany · Department of Theoretical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany

  7. ECG Classification on PTB-XL: A Data-Centric Approach with Simplified CNN-VAE

    Mar 8, 2026Naqcho Ali Mehdi, Amir AliElectrocardiogram ClassificationConvolutional Neural Networks

    NED University of Engineering and Technology, Karachi, Pakistan

  8. Detecting Structural Heart Disease from Electrocardiograms via a Generalized Additive Model of Interpretable Foundation-Model Predictors

    Mar 3, 2026Ya Zhou, Zhaohong Sun, Tianxiang Hao +1Electrocardiogram ClassificationElectrocardiography

    Department of Information Center, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China · The Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China · National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, 100037, China

  9. A Novel end-to-end Digital Health System Using Deep Learning-based ECG Analysis

    Feb 28, 2026Artemis Kontou, Natalia Miroshnikova, Costakis Matheou +4ElectrocardiographyElectrocardiogram Classification

    KIOS Research and Innovation Center of Excellence (KIOS CoE), University of Cyprus, Panepistimiou 1, Aglantzia 2109, Cyprus · MEDTL Medical Technologies Ltd., 91 Limassol Avenue, Aglantzia, Office 202, Nicosia 2121, Cyprus · Department of Computer Science, University of Cyprus, Panepistimiou 1, Aglantzia 2109, Cyprus

  10. RhythmBERT: A Self-Supervised Language Model Based on Latent Representations of ECG Waveforms for Heart Disease Detection

    Feb 26, 2026Xin Wang, Burcu Ozek, Aruna Mohan +3Electrocardiogram Representation LearningElectrocardiogram Foundation Models

    Virginia Tech, VA, USA · Walkky LLC, Boston, MA, USA · Northeastern University, Boston, MA, USA +1

  11. When Should a Model Change Its Mind? An Energy-Based Theory and Regularizer for Concept Drift in Electrocardiogram (ECG) Signals

    Feb 25, 2026Timothy Oladunni, Blessing Ojeme, Kyndal Maclin +1Concept DriftElectrocardiography

    Department of Computer Science, Morgan State University, Baltimore, MD, USA.

  12. Position: Evaluation of ECG Representations Must Be Fixed

    Feb 19, 2026Zachary Berger, Daniel Prakah-Asante, John Guttag +1Electrocardiogram Representation LearningRepresentation Learning

    Massachusetts Institute of Technology, Cambridge, MA, USA · Massachusetts General Hospital, Boston, MA, USA

  13. UCTECG-Net: Uncertainty-aware Convolution Transformer ECG Network for Arrhythmia Detection

    Feb 18, 2026Hamzeh Asgharnezhad, Pegah Tabarisaadi, Abbas Khosravi +2Electrocardiogram ClassificationHybrid CNN-Transformer Architectures

    Deakin University, Australia . · School of Mathematics, Physics and Computing, University of Southern Queensland, Toowoomba, QLD, Australia .

  14. CAMEL: An ECG Language Model for Forecasting Cardiac Events

    Feb 17, 2026Neelay Velingker, Alaia Solko-Breslin, Mayank Keoliya +9Electrocardiogram Foundation ModelsElectrocardiogram Interpretation

    University of Pennsylvania

  15. A Dataset and Benchmarks for Atrial Fibrillation Detection from Electrocardiograms of Intensive Care Unit Patients

    Dec 19, 2025Sarah Nassar, Nooshin Maghsoodi, Sophia Mannina +7Atrial Fibrillation DetectionElectrocardiogram Foundation Models

    Department of Electrical and Computer Engineering at Queen’s University, Kingston, ON, Canada · School of Computing at Queen’s University, Kingston, ON, Canada · Smith School of Business at Queen’s University, Kingston, ON, Canada +5

  16. Investigating ECG Diagnosis with Ambiguous Labels using Partial Label Learning

    Dec 11, 2025Sana Rahmani, Javad Hashemi, Ali EtemadElectrocardiogram Classification

    Electrical and Computer Engineering Department, Queen’s University, Canada · School of Computing, Queen’s University, Canada

  17. FOCAL: Fine-Grained Optimal-Transport-Driven Contrastive Alignment of Language and ECGs with Waveform Enhancement

    May 17, 2025Haitao Li, Che Liu, Zhengyao Ding +3Electrocardiogram ClassificationMultimodal Contrastive Learning

    Zhejiang University · Shanghai Innovation Institute · Imperial College London +2

  18. MambaCapsule: Towards Transparent Cardiac Disease Diagnosis with Electrocardiography Using Mamba Capsule Network

    Jul 30, 2024Yinlong Xu, Zitai Kong, Yixuan Wu +5Interpretable MLElectrocardiogram Classification

    State Key Laboratory of Transvascular Implantation Devices and TIDRI, Zhejiang University, Hangzhou, China · School of Public Health, Zhejiang University and Zhejiang Key Laboratory of Medical Imaging Artificial Intelligence, Hangzhu, China · State Key Laboratory of Transvascular Implantation Devices of The Second Affiliated Hospital and Liangzhu Laboratory, Zhejiang University, Hangzhou, China +3