ECG Datasets

ECG datasets are crucial for developing and evaluating algorithms for automated electrocardiogram interpretation, aiming to improve diagnostic accuracy and efficiency in cardiology. Current research focuses on addressing data imbalances through techniques like self-supervised learning and optimal transport augmentation, and on leveraging deep learning architectures such as convolutional and recurrent neural networks, often combined with large language models for report generation and question answering. These advancements hold significant potential for enhancing clinical decision-making, particularly in detecting rare cardiac anomalies and improving the speed and accuracy of diagnosis.

Papers

September 26, 2024

Ordinary Differential Equations for Enhanced 12-Lead ECG Generation
Yakir Yehuda, Kira Radinsky
Ordinary Differential Equation Synthetic Electrocardiogram ECG Datasets Electrocardiogram Generation

September 13, 2024

Electrocardiogram Report Generation and Question Answering via Retrieval-Augmented Self-Supervised Modeling
Jialu Tang, Tong Xia, Yuan Lu, Cecilia Mascolo, Aaqib Saeed
Yes No Question Retrieval Augmented Medical Information Mart for Intensive Electrocardiogram Recording ECG Datasets

August 30, 2024

Self-supervised Anomaly Detection Pretraining Enhances Long-tail ECG Diagnosis
Aofan Jiang, Chaoqin Huang, Qing Cao, Yuchen Xu, Zi Zeng, Kang Chen, Ya Zhang, Yanfeng Wang
Anomaly Detection Single Lead Electrocardiogram Data ECG Analysis ECG Datasets Electrocardiogram Diagnosis

March 11, 2024

Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement
Che Liu, Zhongwei Wan, Cheng Ouyang, Anand Shah, Wenjia Bai, Rossella Arcucci
Zero Shot Multimodal Learning Electrocardiogram Representation ECG Datasets

February 3, 2024

Transfer Learning in ECG Diagnosis: Is It Effective?
Cuong V. Nguyen, Cuong D. Do
Deep Learning Deep Neural Network Transfer Learning Multi Label ECG Analysis ECG Datasets

June 9, 2023

ElectroCardioGuard: Preventing Patient Misidentification in Electrocardiogram Databases through Neural Networks
Michal Seják, Jakub Sido, David Žahour
Neural Network Patient Data Electrocardiogram Recording Wearable Single Lead Electrocardiogram ECG Datasets

January 23, 2023

ECGAN: Self-supervised generative adversarial network for electrocardiography
Lorenzo Simone, Davide Bacciu
Generative Adversarial Network Self Supervised Synthetic Data State of the Art Generative Synthetic Electrocardiogram ECG Datasets Arrhythmia Classification

January 10, 2023

Analysis of Arrhythmia Classification on ECG Dataset
Taminul Islam, Arindom Kundu, Tanzim Ahmed, Nazmul Islam Khan
General Analysis Electrocardiogram Data ECG Signal ECG Datasets Arrhythmia Type

October 27, 2022

Efficient ECG-based Atrial Fibrillation Detection via Parameterised Hypercomplex Neural Networks
Leonie Basso, Zhao Ren, Wolfgang Nejdl
High Efficiency Wearable Device Atrial Fibrillation Parameterized Hypercomplex Atrial Fibrillation Detection ECG Datasets

August 20, 2022

A Domain Generalization Approach for Out-Of-Distribution 12-lead ECG Classification with Convolutional Neural Networks
Aristotelis Ballas, Christos Diou
Convolutional Neural Network Deep Neural Network Domain Generalization Deep Learning System ECG Datasets Biosignal Classification

February 25, 2022

MetaVA: Curriculum Meta-learning and Pre-fine-tuning of Deep Neural Networks for Detecting Ventricular Arrhythmias based on ECGs
Wenrui Zhang, Shijia Geng, Zhaoji Fu, Linlin Zheng, Chenyang Jiang, Shenda Hong
Deep Neural Network Machine Learning Model Fine Tuning Curriculum Learning Electrocardiogram Recording Arrhythmia Detection ECG Datasets Ventricular Tachycardia

January 25, 2022

Cardiac Disease Diagnosis on Imbalanced Electrocardiography Data Through Optimal Transport Augmentation
Jielin Qiu, Jiacheng Zhu, Mengdi Xu, Peide Huang, Michael Rosenberg, Douglas Weber, Emerson Liu, Ding Zhao
Optimal Transport Data Imbalance ECG Classification ECG Datasets Heart Disease Detection

ECG Datasets

Papers

Ordinary Differential Equations for Enhanced 12-Lead ECG Generation

Electrocardiogram Report Generation and Question Answering via Retrieval-Augmented Self-Supervised Modeling

Self-supervised Anomaly Detection Pretraining Enhances Long-tail ECG Diagnosis

Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement

Transfer Learning in ECG Diagnosis: Is It Effective?

ElectroCardioGuard: Preventing Patient Misidentification in Electrocardiogram Databases through Neural Networks

ECGAN: Self-supervised generative adversarial network for electrocardiography

Analysis of Arrhythmia Classification on ECG Dataset

Efficient ECG-based Atrial Fibrillation Detection via Parameterised Hypercomplex Neural Networks

A Domain Generalization Approach for Out-Of-Distribution 12-lead ECG Classification with Convolutional Neural Networks

MetaVA: Curriculum Meta-learning and Pre-fine-tuning of Deep Neural Networks for Detecting Ventricular Arrhythmias based on ECGs

Cardiac Disease Diagnosis on Imbalanced Electrocardiography Data Through Optimal Transport Augmentation