Arrhythmias

Reduction of false arrhythmia alarms using signal selection and machine learning.

In this paper, we propose an algorithm that classifies whether a generated cardiac arrhythmia alarm is true or false. The large number of false alarms in intensive care is a severe issue. The noise peaks caused by alarms can be high and in a noisy environment nurses can experience stress and fatigue. In addition, patient safety is compromised because reaction time of the caregivers to true alarms ...

Reducing false alarms in the ICU by quantifying self-similarity of multimodal biosignals.

False arrhythmia alarms pose a major threat to the quality of care in today's ICU. Thus, the PhysioNet/Computing in Cardiology Challenge 2015 aimed at reducing false alarms by exploiting multimodal cardiac signals recorded by a patient monitor. False alarms for asystole, extreme bradycardia, extreme tachycardia, ventricular flutter/fibrillation as well as ventricular tachycardia were to be reduced...

Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators.

Early recognition of ventricular fibrillation (VF) and electrical therapy are key for the survival of out-of-hospital cardiac arrest (OHCA) patients t...

ADMET Evaluation in Drug Discovery. 16. Predicting hERG Blockers by Combining Multiple Pharmacophores and Machine Learning Approaches.

Blockade of human ether-à-go-go related gene (hERG) channel by compounds may lead to drug-induced QT prolongation, arrhythmia, and Torsades de Pointes...

Efficient Fine Arrhythmia Detection Based on DCG P-T Features.

Due to the high mortality associated with heart disease, there is an urgent demand for advanced detection of abnormal heart beats. The use of dynamic ...

Improved Prediction of Drug-Induced Torsades de Pointes Through Simulations of Dynamics and Machine Learning Algorithms.

The ventricular arrhythmia Torsades de Pointes (TdP) is a common form of drug-induced cardiotoxicity, but prediction of this arrhythmia remains an unr...

Semi-supervised clustering of fractionated electrograms for electroanatomical atrial mapping.

BACKGROUND: Electrogram-guided ablation procedures have been proposed as an alternative strategy consisting of either mapping and ablating focal sourc...

Ready-to-use parenteral amiodarone: a feasibility study towards a long-term stable product formulation.

OBJECTIVES: To determine the feasibility of preparing a long-term stable ready-to-use parenteral amiodarone formulation using cyclodextrins as dissolu...

ICEPO: the ion channel electrophysiology ontology.

Ion channels are transmembrane proteins that selectively allow ions to flow across the plasma membrane and play key roles in diverse biological proces...

Mechanisms of memory storage in a model perirhinal network.

The perirhinal cortex supports recognition and associative memory. Prior unit recording studies revealed that recognition memory involves a reduced re...

High-Performance Personalized Heartbeat Classification Model for Long-Term ECG Signal.

Long-term electrocardiogram (ECG) has become one of the important diagnostic assist methods in clinical cardiovascular domain. Long-term ECG is primar...

Medical Decision Support System for Diagnosis of Heart Arrhythmia using DWT and Random Forests Classifier.

In this study, Random Forests (RF) classifier is proposed for ECG heartbeat signal classification in diagnosis of heart arrhythmia. Discrete wavelet t...

Combining Amplitude Spectrum Area with Previous Shock Information Using Neural Networks Improves Prediction Performance of Defibrillation Outcome for Subsequent Shocks in Out-Of-Hospital Cardiac Arrest Patients.

OBJECTIVE: Quantitative ventricular fibrillation (VF) waveform analysis is a potentially powerful tool to optimize defibrillation. However, whether co...

Comparison of Support-Vector Machine and Sparse Representation Using a Modified Rule-Based Method for Automated Myocardial Ischemia Detection.

An automatic method is presented for detecting myocardial ischemia, which can be considered as the early symptom of acute coronary events. Myocardial ...

Symbolic features and classification via support vector machine for predicting death in patients with Chagas disease.

This paper introduces a technique for predicting death in patients with Chagas disease using features extracted from symbolic series and time-frequenc...

Detection of Shockable Ventricular Arrhythmia using Variational Mode Decomposition.

Ventricular tachycardia (VT) and ventricular fibrillation (VF) are shockable ventricular cardiac ailments. Detection of VT/VF is one of the important ...

Wavelet-based unsupervised learning method for electrocardiogram suppression in surface electromyograms.

We present a novel approach aimed at removing electrocardiogram (ECG) perturbation from single-channel surface electromyogram (EMG) recordings by mean...

Percutaneous Ultrasound-Guided Laser Ablation with Contrast-Enhanced Ultrasonography for Hyperfunctioning Parathyroid Adenoma: A Preliminary Case Series.

The study was to evaluate the safety and effectiveness of ultrasound-guided percutaneous laser ablation (pLA) as a nonsurgical treatment for primary p...

Superiority of Classification Tree versus Cluster, Fuzzy and Discriminant Models in a Heartbeat Classification System.

This study presents a 2-stage heartbeat classifier of supraventricular (SVB) and ventricular (VB) beats. Stage 1 makes computationally-efficient class...

Arrhythmia ablation using the Amigo Robotic Remote Catheter System versus manual ablation: One year follow-up results.