Practical lessons on 12-lead ECG classification: Meta-analysis of methods from PhysioNet/computing in cardiology challenge 2020
Cardiovascular diseases (CVDs) are one of the most fatal disease groups worldwide.
Electrocardiogram (ECG) is a widely used tool for automatically detecting cardiac …
Electrocardiogram (ECG) is a widely used tool for automatically detecting cardiac …
Improving explainability of deep neural network-based electrocardiogram interpretation using variational auto-encoders
RR van de Leur, MN Bos, K Taha… - … Heart Journal-Digital …, 2022 - academic.oup.com
Abstract Aims Deep neural networks (DNNs) perform excellently in interpreting
electrocardiograms (ECGs), both for conventional ECG interpretation and for novel …
electrocardiograms (ECGs), both for conventional ECG interpretation and for novel …
HRIDM: Hybrid Residual/Inception-Based Deeper Model for Arrhythmia Detection from Large Sets of 12-Lead ECG Recordings
Heart diseases such as cardiovascular and myocardial infarction are the foremost reasons
of death in the world. The timely, accurate, and effective prediction of heart diseases is …
of death in the world. The timely, accurate, and effective prediction of heart diseases is …
Automatic Classification of Cardiac Arrhythmias using Deep Learning Techniques: A Systematic Review
F Vásquez-Iturralde, M Flores-Calero… - IEEE …, 2024 - ieeexplore.ieee.org
Cardiac arrhythmias are one of the main causes of death worldwide; therefore, early
detection is essential to save the lives of patients who suffer from them and to reduce the …
detection is essential to save the lives of patients who suffer from them and to reduce the …
Electrocardiogram-based mortality prediction in patients with COVID-19 using machine learning
RR Van de Leur, H Bleijendaal, K Taha, T Mast… - Netherlands Heart …, 2022 - Springer
Background and purpose The electrocardiogram (ECG) is frequently obtained in the work-
up of COVID-19 patients. So far, no study has evaluated whether ECG-based machine …
up of COVID-19 patients. So far, no study has evaluated whether ECG-based machine …
Deep neural networks reveal novel sex-specific electrocardiographic features relevant for mortality risk
KR Siegersma, RR Van De Leur… - … Heart Journal-Digital …, 2022 - academic.oup.com
Aims Incorporation of sex in study design can lead to discoveries in medical research. Deep
neural networks (DNNs) accurately predict sex based on the electrocardiogram (ECG) and …
neural networks (DNNs) accurately predict sex based on the electrocardiogram (ECG) and …
Introduction and comparison of novel decentral learning schemes with multiple data pools for privacy-preserving ECG classification
Artificial intelligence and machine learning have led to prominent and spectacular
innovations in various scenarios. Application in medicine, however, can be challenging due …
innovations in various scenarios. Application in medicine, however, can be challenging due …
Application of federated learning techniques for arrhythmia classification using 12-lead ecg signals
DM Jimenez Gutierrez, HM Hassan, L Landi… - … on Algorithmic Aspects …, 2023 - Springer
Artificial Intelligence-based (AI) analysis of large, curated medical datasets is promising for
providing early detection, faster diagnosis, and more effective treatment using low-power …
providing early detection, faster diagnosis, and more effective treatment using low-power …
Inherently explainable deep neural network-based interpretation of electrocardiograms using variational auto-encoders
Abstract Background Deep neural networks (DNNs) show excellent performance in
interpreting electrocardiograms (ECGs), both for conventional ECG interpretation and for …
interpreting electrocardiograms (ECGs), both for conventional ECG interpretation and for …
Check for updates Application of Federated Learning Techniques for Arrhythmia Classification Using 12-Lead ECG Signals
DMJ Gutierrez, HM Hassan, L Landi… - … Aspects of Cloud …, 2023 - books.google.com
Artificial Intelligence-based (AI) analysis of large, curated medical datasets is promising for
providing early detection, faster diagnosis, and more effective treatment using low-power …
providing early detection, faster diagnosis, and more effective treatment using low-power …