Arrhythmias

Combining Low-dimensional Wavelet Features and Support Vector Machine for Arrhythmia Beat Classification.

Automatic feature extraction and classification are two main tasks in abnormal ECG beat recognition. Feature extraction is an important prerequisite prior to classification since it provides the classifier with input features, and the performance of classifier depends significantly on the quality of these features. This study develops an effective method to extract low-dimensional ECG beat feature...

Ablation Index and Surround Flow Catheter Irrigation: Impedance-Based Appraisal in Clinical Ablation.

OBJECTIVES: This study sought to assess the impact of ablation power and catheter irrigation during clinical radiofrequency ablation using impedance drop.

Classification of ECG heartbeats using nonlinear decomposition methods and support vector machine.

Classifying electrocardiogram (ECG) heartbeats for arrhythmic risk prediction is a challenging task due to minute variations in the amplitude, duratio...

What Is High Enough? Elevated NT-pro-BNP in Decompensated Paroxysmal Supraventricular Tachycardia.

Since the late 1980s, elevated atrial natriuretic peptide (ANP) was considered the cause of brisk diuresis in adult patients with paroxysmal supravent...

Premature ventricular contraction detection combining deep neural networks and rules inference.

Premature ventricular contraction (PVC), which is a common form of cardiac arrhythmia caused by ectopic heartbeat, can lead to life-threatening cardia...

Performance of Machine Learning Algorithms for Qualitative and Quantitative Prediction Drug Blockade of hERG1 channel.

Drug-induced abnormal heart rhythm known as (TdP) is a potential lethal ventricular tachycardia found in many patients. Even newly released anti-arrh...

Patient-Specific Deep Architectural Model for ECG Classification.

Heartbeat classification is a crucial step for arrhythmia diagnosis during electrocardiographic (ECG) analysis. The new scenario of wireless body sens...

Radiofrequency Ablation Followed by Percutaneous Ethanol Ablation Leading to Long-Term Remission of Hyperparathyroidism.

A 30-year-old male with cerebral palsy and motor impairment presented with right femur fracture. He had gradually worsening mobility and contractures ...

Automated diagnosis of congestive heart failure using dual tree complex wavelet transform and statistical features extracted from 2s of ECG signals.

Identification of alarming features in the electrocardiogram (ECG) signal is extremely significant for the prediction of congestive heart failure (CHF...

Disease-free survival assessment by artificial neural networks for hepatocellular carcinoma patients after radiofrequency ablation.

BACKGROUND/PURPOSE: Radiofrequency ablation (RFA) provides an effective treatment for patients who exhibit early hepatocellular carcinoma (HCC) stages...

Reducing false arrhythmia alarm rates using robust heart rate estimation and cost-sensitive support vector machines.

To lessen the rate of false critical arrhythmia alarms, we used robust heart rate estimation and cost-sensitive support vector machines. The PhysioNet...

Risk factors associated with high thyroglobulin level following radioactive iodine ablation, measured 12 months after treatment for papillary thyroid carcinoma.

PURPOSE: The measurement of serum thyroglobulin (Tg) of papillary thyroid carcinoma patients, 12 months after total thyroidectomy and radioactive iodi...

Substantial superiority of Niobe ES over Niobe II system in remote-controlled magnetic pulmonary vein isolation.

BACKGROUND: Catheter ablation of atrial fibrillation (AFib) primarily relies upon pulmonary vein isolation (PVI), but such procedures are associated w...

Runtime Verification of Pacemaker Functionality Using Hierarchical Fuzzy Colored Petri-nets.

Today, implanted medical devices are increasingly used for many patients and in case of diverse health problems. However, several runtime problems and...

Prescription of Guideline-Recommended Implantable Cardioverter Defibrillator and Cardiac Resynchronization Therapy Among Patients Hospitalized With Heart Failure and Varying Degrees of Renal Function.

Implantable cardioverter defibrillators (ICD) and cardiac resynchronization therapy (CRT) reduce mortality in many patients with heart failure (HF), b...

A novel algorithm for ventricular arrhythmia classification using a fuzzy logic approach.

In the present study, it has been shown that an unnecessary implantable cardioverter-defibrillator (ICD) shock is often delivered to patients with an ...

A novel machine learning-enabled framework for instantaneous heart rate monitoring from motion-artifact-corrupted electrocardiogram signals.

This paper proposes a novel machine learning-enabled framework to robustly monitor the instantaneous heart rate (IHR) from wrist-electrocardiography (...

Relationship between right and left ventricular function in candidates for implantable cardioverter defibrillator with low left ventricular ejection fraction.

BACKGROUND: Indications for the primary prevention of sudden death using an implantable cardioverter defibrillator (ICD) are based predominantly on le...

Prediction of Ventricular Tachycardia One Hour before Occurrence Using Artificial Neural Networks.

Ventricular tachycardia (VT) is a potentially fatal tachyarrhythmia, which causes a rapid heartbeat as a result of improper electrical activity of the...

Suppression of false arrhythmia alarms in the ICU: a machine learning approach.

This paper presents a novel approach for false alarm suppression using machine learning tools. It proposes a multi-modal detection algorithm to find t...