Arrhythmias

Machine learning versus traditional methods for the development of risk stratification scores: a case study using original Canadian Syncope Risk Score data.

Artificial Intelligence and machine learning (ML) methods are promising for risk-stratification, but...

Outcomes of Salvage Robot-assisted Radical Prostatectomy After Focal Ablation for Prostate Cancer in Comparison to Primary Robot-assisted Radical Prostatectomy: A Matched Analysis.

BACKGROUND: Focal therapy (FT) for prostate cancer is less invasive than radical treatment but carri...

Classification of electrocardiogram signals with waveform morphological analysis and support vector machines.

Electrocardiogram (ECG) indicates the occurrence of various cardiac diseases, and the accurate class...

Review of Deep Learning-Based Atrial Fibrillation Detection Studies.

Atrial fibrillation (AF) is a common arrhythmia that can lead to stroke, heart failure, and prematur...

Optimal ECG-lead selection increases generalizability of deep learning on ECG abnormality classification.

Deep learning (DL) has achieved promising performance in detecting common abnormalities from the 12-...

Robustness of convolutional neural networks to physiological electrocardiogram noise.

The electrocardiogram (ECG) is a widespread diagnostic tool in healthcare and supports the diagnosis...

A community effort to assess and improve computerized interpretation of 12-lead resting electrocardiogram.

Computerized interpretation of electrocardiogram plays an important role in daily cardiovascular hea...

Effect of Lamotrigine on Ouabain-Induced Arrhythmia in Isolated Atria of Guinea Pigs.

Lamotrigine (LTG) is an antiepileptic drug used in the treatment of seizures, mood disorders, and c...

Deep Learning-Based Computed Tomography Imaging to Diagnose the Lung Nodule and Treatment Effect of Radiofrequency Ablation.

This study aimed to detect and diagnose the lung nodules as early as possible to effectively treat t...

Prediction of In Vivo Laser-Induced Thermal Damage with Hyperspectral Imaging Using Deep Learning.

Thermal ablation is an acceptable alternative treatment for primary liver cancer, of which laser abl...

Classification of Arrhythmia in Heartbeat Detection Using Deep Learning.

The electrocardiogram (ECG) is one of the most widely used diagnostic instruments in medicine and he...

Pushing the Limits of the ECG: Can We Assess Biventricular Function Without Imaging?

Rationale and design of the SafeHeart study: Development and testing of a mHealth tool for the prediction of arrhythmic events and implantable cardioverter-defibrillator therapy.

BACKGROUND: Patients with an implantable cardioverter-defibrillator (ICD) are at a high risk of mali...

The BrAID study protocol: integration of machine learning and transcriptomics for brugada syndrome recognition.

BACKGROUND: Type 1 Brugada syndrome (BrS) is a hereditary arrhythmogenic disease showing peculiar el...

Deep Learning-Based Recurrence Prediction of Atrial Fibrillation After Catheter Ablation.

BACKGROUND: Radiofrequency catheter ablation (RFCA) is an effective therapy for atrial fibrillation ...

ML-Net: Multi-Channel Lightweight Network for Detecting Myocardial Infarction.

Due to the complexity of myocardial infarction (MI) waveform, most traditional automatic diagnosis m...

Information fusion and multi-classifier system for miner fatigue recognition in plateau environments based on electrocardiography and electromyography signals.

BACKGROUND AND OBJECTIVE: Human factors are important contributors to accidents, especially human er...

Machine learning-based risk prediction of malignant arrhythmia in hospitalized patients with heart failure.

AIMS: Predicting the risk of malignant arrhythmias (MA) in hospitalized patients with heart failure ...

Artificial intelligence in ECG screening: Ready for prime time?

Paroxysmal atrial fibrillation prediction based on morphological variant P-wave analysis with wideband ECG and deep learning.

BACKGROUND AND OBJECTIVE: Atrial fibrillation (AF) is one of the most frequent asymptomatic arrhythm...

ECG-based machine-learning algorithms for heartbeat classification.

Electrocardiogram (ECG) signals represent the electrical activity of the human hearts and consist of...