Cardiovascular

Arrhythmias

Latest AI and machine learning research in arrhythmias for healthcare professionals.

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An Effective LSTM Recurrent Network to Detect Arrhythmia on Imbalanced ECG Dataset.

To reduce the high mortality rate from cardiovascular disease (CVD), the electrocardiogram (ECG) bea...

Inter-Patient ECG Classification With Symbolic Representations and Multi-Perspective Convolutional Neural Networks.

This paper presents a novel deep learning framework for the inter-patient electrocardiogram (ECG) he...

Detection and Monitoring of Thermal Lesions Induced by Microwave Ablation Using Ultrasound Imaging and Convolutional Neural Networks.

Microwave ablation (MWA) for cancer treatment is frequently monitored by ultrasound (US) B-mode imag...

CT Texture Analysis and Machine Learning Improve Post-ablation Prognostication in Patients with Adrenal Metastases: A Proof of Concept.

INTRODUCTION: To assess the performance of pre-ablation computed tomography texture features of adre...

Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery.

BACKGROUND: The ECG remains the most widely used diagnostic test for characterization of cardiac str...

Age and Sex Estimation Using Artificial Intelligence From Standard 12-Lead ECGs.

BACKGROUND: Sex and age have long been known to affect the ECG. Several biologic variables and anato...

Design and control of a MRI-compatible pneumatic needle puncture robot.

Percutaneous needle puncture operation is widely used in the image-guided interventions, including b...

Synthesis of Electrocardiogram V-Lead Signals From Limb-Lead Measurement Using R-Peak Aligned Generative Adversarial Network.

Recently, portable electrocardiogram (ECG) hardware devices have been developed using limb-lead meas...

A modeling and machine learning approach to ECG feature engineering for the detection of ischemia using pseudo-ECG.

Early detection of coronary heart disease (CHD) has the potential to prevent the millions of deaths ...

Cardiac arrhythmia detection using deep learning: A review.

Due to its simplicity and low cost, analyzing an electrocardiogram (ECG) is the most common techniqu...

Accurate detection of atrial fibrillation from 12-lead ECG using deep neural network.

Atrial fibrillation (AF) is the most common heart arrhythmia, and 12-lead electrocardiogram (ECG) is...

Non-contact heart and respiratory rate monitoring of preterm infants based on a computer vision system: a method comparison study.

BACKGROUND: Non-contact heart rate (HR) and respiratory rate (RR) monitoring is necessary for preter...

Energy-Efficient Intelligent ECG Monitoring for Wearable Devices.

Wearable intelligent ECG monitoring devices can perform automatic ECG diagnosis in real time and sen...

A Novel Approach for Multi-Lead ECG Classification Using DL-CCANet and TL-CCANet.

Cardiovascular disease (CVD) has become one of the most serious diseases that threaten human health....

Identifying signal-dependent information about the preictal state: A comparison across ECoG, EEG and EKG using deep learning.

BACKGROUND: The inability to reliably assess seizure risk is a major burden for epilepsy patients an...

A Real-Time Arrhythmia Heartbeats Classification Algorithm Using Parallel Delta Modulations and Rotated Linear-Kernel Support Vector Machines.

Real-time wearable electrocardiogram monitoring sensor is one of the best candidates in assisting ca...

Electrocardiogram Classification Based on Faster Regions with Convolutional Neural Network.

The classification of electrocardiograms (ECG) plays an important role in the clinical diagnosis of ...

Combining deep neural networks and engineered features for cardiac arrhythmia detection from ECG recordings.

OBJECTIVE: We aim to combine deep neural networks and engineered features (hand-crafted features bas...

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