Arrhythmias

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...

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...

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...

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...

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...

Explaining deep neural networks for knowledge discovery in electrocardiogram analysis.

Deep learning-based tools may annotate and interpret medical data more quickly, consistently, and ac...

Impact of ECG Characteristics on the Performance of an Artificial Intelligence Enabled ECG for Predicting Left Ventricular Dysfunction.

The application of deep learning in electrocardiogram: Where we came from and where we should go?

Electrocardiogram (ECG) is a commonly-used, non-invasive examination recording cardiac voltage versu...

Artificial intelligence-enabled fully automated detection of cardiac amyloidosis using electrocardiograms and echocardiograms.

Patients with rare conditions such as cardiac amyloidosis (CA) are difficult to identify, given the ...

Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL.

Electrocardiography (ECG) is a very common, non-invasive diagnostic procedure and its interpretation...

AECG-DecompNet: abdominal ECG signal decomposition through deep-learning model.

The accurate decomposition of a mother's abdominal electrocardiogram (AECG) to extract the fetal ECG...

Artificial intelligence-enabled electrocardiograms for identification of patients with low ejection fraction: a pragmatic, randomized clinical trial.

We have conducted a pragmatic clinical trial aimed to assess whether an electrocardiogram (ECG)-base...

An artificial intelligence-enabled ECG algorithm for comprehensive ECG interpretation: Can it pass the 'Turing test'?

OBJECTIVE: To develop an artificial intelligence (AI)-enabled electrocardiogram (ECG) algorithm capa...

ECG Heartbeat Classification Based on an Improved ResNet-18 Model.

Based on a convolutional neural network (CNN) approach, this article proposes an improved ResNet-18 ...

Automated ECG classification based on 1D deep learning network.

The standard 12-lead electrocardiogram (ECG) records the heart's electrical activity from electrodes...

A fused-image-based approach to detect obstructive sleep apnea using a single-lead ECG and a 2D convolutional neural network.

Obstructive sleep apnea (OSA) is a common chronic sleep disorder that disrupts breathing during slee...

A deep learning approach for 2D ultrasound and 3D CT/MR image registration in liver tumor ablation.

BACKGROUND AND OBJECTIVE: Liver tumor ablation is often guided by ultrasound (US). Due to poor image...