Arrhythmias

Electrocardiogram-Based Emotion Recognition Systems and Their Applications in Healthcare-A Review.

Affective computing is a field of study that integrates human affects and emotions with artificial i...

Artificial Intelligence-Enabled ECG to Identify Silent Atrial Fibrillation in Embolic Stroke of Unknown Source.

OBJECTIVES: Embolic strokes of unknown source (ESUS) are common and often suspected to be caused by ...

Practical fine-grained learning based anomaly classification for ECG image.

As a widely used vital sign within cardiology, Electrocardiography (ECG) provides the basis for asse...

xECGNet: Fine-tuning attention map within convolutional neural network to improve detection and explainability of concurrent cardiac arrhythmias.

Background and objectiveDetecting abnormal patterns within an electrocardiogram (ECG) is crucial for...

MEGnet: Automatic ICA-based artifact removal for MEG using spatiotemporal convolutional neural networks.

Magnetoencephalography (MEG) is a functional neuroimaging tool that records the magnetic fields indu...

Robotic guidance platform for laser interstitial thermal ablation and stereotactic needle biopsies: a single center experience.

While laser ablation has become an increasingly important tool in the neurosurgical oncologist's arm...

ECG quality assessment based on hand-crafted statistics and deep-learned S-transform spectrogram features.

Background and Objective Electrocardiogram (ECG) quality assessment is significant for automatic dia...

The Role of Artificial Intelligence in Arrhythmia Monitoring.

Arrhythmia management has been revolutionized by the ability to monitor the cardiac rhythm in a pati...

The effect of cardiac rhythm on artificial intelligence-enabled ECG evaluation of left ventricular ejection fraction prediction in cardiac intensive care unit patients.

The presence of left ventricular systolic dysfunction (LVSD) alters clinical management and prognosi...

ECG Signal Modeling Using Volatility Properties: Its Application in Sleep Apnea Syndrome.

This study presents and evaluates the mathematical model to estimate the mean and variance of single...

Combined deep CNN-LSTM network-based multitasking learning architecture for noninvasive continuous blood pressure estimation using difference in ECG-PPG features.

The pulse arrival time (PAT), the difference between the R-peak time of electrocardiogram (ECG) sign...

Obstructive sleep apnea prediction from electrocardiogram scalograms and spectrograms using convolutional neural networks.

In this study, we conducted a comparative analysis of deep convolutional neural network (CNN) models...

Detection and classification of arrhythmia using an explainable deep learning model.

BACKGROUND: Early detection and intervention is the cornerstone for appropriate treatment of arrhyth...

A new deep learning algorithm of 12-lead electrocardiogram for identifying atrial fibrillation during sinus rhythm.

Atrial fibrillation (AF) is the most prevalent arrhythmia and is associated with increased morbidity...

Machine Learning for ECG Diagnosis of LV Dysfunction.

A Soft Resistive Sensor with a Semicircular Cross-Sectional Channel for Soft Cardiac Catheter Ablation.

The field of soft robotics has attracted the interest of the medical community due to the ability of...

ECG for Screening Cardiac Abnormalities: The Premise and Promise of Machine Learning.

Integrating ECG Monitoring and Classification via IoT and Deep Neural Networks.

Anesthesia assessment is most important during surgery. Anesthesiologists use electrocardiogram (ECG...

Automatic coronary artery calcium scoring from unenhanced-ECG-gated CT using deep learning.

PURPOSE: The purpose of this study was to develop and evaluate an algorithm that can automatically e...

Classification of Mental Stress Using CNN-LSTM Algorithms with Electrocardiogram Signals.

The mental stress faced by many people in modern society is a factor that causes various chronic dis...

Salvage Robot-assisted Renal Surgery for Local Recurrence After Surgical Resection or Renal Mass Ablation: Classification, Techniques, and Clinical Outcomes.

BACKGROUND: Salvage treatment for local recurrence after prior partial nephrectomy (PN) or local tum...