Arrhythmias

Cold ablation robot-guided laser osteotomy in hand, wrist and forearm surgery-A feasibility study.

INTRODUCTION: Traditional bone surgery using saws and chisels is associated with direct contact of i...

A Modified Deep Learning Framework for Arrhythmia Disease Analysis in Medical Imaging Using Electrocardiogram Signal.

Arrhythmias are anomalies in the heartbeat rhythm that occur occasionally in people's lives. These a...

A Multimodal AI System for Out-of-Distribution Generalization of Seizure Identification.

Artificial intelligence (AI) and health sensory data-fusion hold the potential to automate many labo...

An Explainable Transformer-Based Deep Learning Model for the Prediction of Incident Heart Failure.

Predicting the incidence of complex chronic conditions such as heart failure is challenging. Deep le...

Electrocardiogram analysis of post-stroke elderly people using one-dimensional convolutional neural network model with gradient-weighted class activation mapping.

Stroke is the second leading cause of death globally after ischemic heart disease, also a risk facto...

Neural Network Detection of Pacemakers for MRI Safety.

Flagging the presence of cardiac devices such as pacemakers before an MRI scan is essential to allow...

Artificial Intelligence-Enabled ECG: Physiologic and Pathophysiologic Insights and Implications.

Advancements in machine learning and computing methods have given new life and great excitement to o...

Comparison of neural basis expansion analysis for interpretable time series (N-BEATS) and recurrent neural networks for heart dysfunction classification.

The primary purpose of this work is to analyze the ability of N-BEATS architecture for the problem o...

Automatic ECG classification and label quality in training data.

Within the PhysioNet/Computing in Cardiology Challenge 2021, we focused on the design of a machine l...

Heart age estimated using explainable advanced electrocardiography.

Electrocardiographic (ECG) Heart Age conveying cardiovascular risk has been estimated by both Bayesi...

Cost-Sensitive Learning for Anomaly Detection in Imbalanced ECG Data Using Convolutional Neural Networks.

Arrhythmia detection algorithms based on deep learning are attracting considerable interest due to t...

Deepaware: A hybrid deep learning and context-aware heuristics-based model for atrial fibrillation detection.

BACKGROUND: State-of-the-art automatic atrial fibrillation (AF) detection models trained on RR-inter...

A Neuromorphic Model With Delay-Based Reservoir for Continuous Ventricular Heartbeat Detection.

There is a growing interest in neuromorphic hardware since it offers a more intuitive way to achieve...

An Energy Efficient ECG Ventricular Ectopic Beat Classifier Using Binarized CNN for Edge AI Devices.

Wearable Artificial Intelligence-of-Things (AIoT) requires edge devices to be resource and energy-ef...

Artificial Intelligence in Electrocardiology for Arrhythmia Diagnosis.

ECG classification system based on multi-domain features approach coupled with least square support vector machine (LS-SVM).

Developing a robust authentication and identification method becomes an urgent demand to protect the...

[Artificial intelligence-based ECG analysis: current status and future perspectives-Part 2 : Recent studies and future].

While fundamental aspects of the application of artificial intelligence (AI) to electrocardiogram (E...

[Artificial intelligence-based ECG analysis: current status and future perspectives-Part 1 : Basic principles].

Even though electrocardiography is a diagnostic procedure that is now more than 100 years old, medic...

rECHOmmend: An ECG-Based Machine Learning Approach for Identifying Patients at Increased Risk of Undiagnosed Structural Heart Disease Detectable by Echocardiography.

BACKGROUND: Timely diagnosis of structural heart disease improves patient outcomes, yet many remain ...

ANNet: A Lightweight Neural Network for ECG Anomaly Detection in IoT Edge Sensors.

In this paper, we propose a lightweight neural network for real-time electrocardiogram (ECG) anomaly...

Exploiting exercise electrocardiography to improve early diagnosis of atrial fibrillation with deep learning neural networks.

Atrial fibrillation (AF) is the most common type of sustained arrhythmia. It results from abnormal i...