Arrhythmias

The Identification of ECG Signals Using WT-UKF and IPSO-SVM.

The biometric identification method is a current research hotspot in the pattern recognition field. ...

LDIAED: A lightweight deep learning algorithm implementable on automated external defibrillators.

Differentiating between shockable and non-shockable Electrocardiogram (ECG) signals would increase t...

A regularization method to improve adversarial robustness of neural networks for ECG signal classification.

With the advancement of machine leaning technologies, Deep Neural Networks (DNNs) have been utilized...

Compressed Deep Learning to Classify Arrhythmia in an Embedded Wearable Device.

The importance of an embedded wearable device with automatic detection and alarming cannot be overst...

Reply to Francesco Montorsi, Armando Stabile, Giorgio Gandaglia, and Alberto Briganti's Letter to the Editor re: K.R. Seetharam Bhat, Marcio Covas Moschovas, Marco Sandri, et al. Outcomes of Salvage Robot-assisted Radical Prostatectomy After Focal Ablation for Prostate Cancer in Comparison to Primary Robot-assisted Radical Prostatectomy: A Matched Analysis. Eur Urol Focus. In press. https://doi.org/10.1016/j.euf.2021.10.005: Salvage Robotic Radical Prostatectomy for Recurrence After Focal Therapy-The Truth and Consequences.

Deep Learning-Based Emergency Care Process Reengineering of Interventional Data for Patients with Emergency Time-Series Events of Myocardial Infarction.

This paper proposes a representation learning framework HE-LSTM model for heterogeneous temporal eve...

Re: K.R. Seetharam Bhat, Marcio Covas Moschovas, Marco Sandri, et al. Outcomes of Salvage Robot-assisted Radical Prostatectomy After Focal Ablation for Prostate Cancer in Comparison to Primary Robot-assisted Radical Prostatectomy: A Matched Analysis. Eur Urol Focus. In press. https://doi.org/10.1016/j.euf.2021.10.005.

EP-PINNs: Cardiac Electrophysiology Characterisation Using Physics-Informed Neural Networks.

Accurately inferring underlying electrophysiological (EP) tissue properties from action potential re...

Optimal Classification of Atrial Fibrillation and Congestive Heart Failure Using Machine Learning.

Cardiovascular disorders, including atrial fibrillation (AF) and congestive heart failure (CHF), are...

Arterial enhancing local tumor progression detection on CT images using convolutional neural network after hepatocellular carcinoma ablation: a preliminary study.

To evaluate the performance of a deep convolutional neural network (DCNN) in detecting local tumor p...

Electrocardiogram Signal Classification in the Diagnosis of Heart Disease Based on RBF Neural Network.

Heart disease is a common disease affecting human health. Electrocardiogram (ECG) classification is ...

Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient-Specific Left Atrial Models.

BACKGROUND: Current ablation therapy for atrial fibrillation is suboptimal, and long-term response i...

A VLSI Chip for the Abnormal Heart Beat Detection Using Convolutional Neural Network.

The heart is one of the human body's vital organs. An electrocardiogram (ECG) provides continuous tr...

Evaluation of Maturation in Preterm Infants Through an Ensemble Machine Learning Algorithm Using Physiological Signals.

This study was designed to test if heart rate variability (HRV) data from preterm and full-term infa...

A novel graph convolutional neural network for predicting interaction sites on protein kinase inhibitors in phosphorylation.

Protein kinase-inhibitor interactions are key to the phosphorylation of proteins involved in cell pr...

Artificial intelligence predicts clinically relevant atrial high-rate episodes in patients with cardiac implantable electronic devices.

To assess the utility of machine learning (ML) algorithms in predicting clinically relevant atrial h...

ECG-BiCoNet: An ECG-based pipeline for COVID-19 diagnosis using Bi-Layers of deep features integration.

The accurate and speedy detection of COVID-19 is essential to avert the fast propagation of the viru...

Bayesian-based optimized deep learning model to detect COVID-19 patients using chest X-ray image data.

Coronavirus Disease 2019 (COVID-19) is extremely infectious and rapidly spreading around the globe. ...

Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study.

BACKGROUND: Most patients who have heart failure with a reduced ejection fraction, when left ventric...

Towards an artificial intelligence-augmented, ECG-enabled physical exam.

System on Chip (SoC) for Invisible Electrocardiography (ECG) Biometrics.

Biometric identification systems are a fundamental building block of modern security. However, conve...