Cardiovascular

Arrhythmias

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

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Showing 232-252 of 1,699 articles
Rhythm-Ready: Harnessing Smart Devices to Detect and Manage Arrhythmias.

PURPOSE OF REVIEW: To survey recent progress in the application of implantable and wearable sensors ...

Deep learning assists early-detection of hypertension-mediated heart change on ECG signals.

Arterial hypertension is a major risk factor for cardiovascular diseases. While cardiac ultrasound i...

Serum Potassium Monitoring UsingĀ AI-Enabled Smartwatch Electrocardiograms.

BACKGROUND: Hyperkalemia, characterized by elevated serum potassium levels, heightens the risk of su...

ECG classification based on guided attention mechanism.

BACKGROUND AND OBJECTIVE: Integrating domain knowledge into deep learning models can improve their e...

Visual interpretation of deep learning model in ECG classification: A comprehensive evaluation of feature attribution methods.

Feature attribution methods can visually highlight specific input regions containing influential asp...

An Arrhythmia Classification Model Based on a CNN-LSTM-SE Algorithm.

Arrhythmia is the main cause of sudden cardiac death, and ECG signal analysis is a common method for...

Deep residual 2D convolutional neural network for cardiovascular disease classification.

Cardiovascular disease (CVD) continues to be a major global health concern, underscoring the need fo...

Development and validation of a machine learning model to predict myocardial blood flow and clinical outcomes from patients' electrocardiograms.

We develop a machine learning (ML) model using electrocardiography (ECG) to predict myocardial blood...

Study on microwave ablation temperature prediction model based on grayscale ultrasound texture and machine learning.

BACKGROUND: Temperature prediction is crucial in the clinical ablation treatment of liver cancer, as...

CardioGuard: AI-driven ECG authentication hybrid neural network for predictive health monitoring in telehealth systems.

The increasing integration of telehealth systems underscores the importance of robust and secure met...

Artificial intelligence-enhanced electrocardiogram for the diagnosis of cardiac amyloidosis: A systemic review and meta-analysis.

BACKGROUND: Diagnosis of cardiac amyloidosis (CA) is often delayed due to variability in clinical pr...

Inferring ECG Waveforms from PPG Signals with a Modified U-Net Neural Network.

There are two widely used methods to measure the cardiac cycle and obtain heart rate measurements: t...

Effective cardiac disease classification using FS-XGB and GWO approach.

Globally, cardiovascular diseases (CVDs) are a leading cause of death; however, their impact can be ...

Image-based ECG analyzing deep-learning algorithm to predict biological age and mortality risks: interethnic validation.

BACKGROUND: Cardiovascular risk assessment is a critical component of healthcare, guiding preventive...

Precise ablation zone segmentation on CT images after liver cancer ablation using semi-automatic CNN-based segmentation.

BACKGROUND: Ablation zone segmentation in contrast-enhanced computed tomography (CECT) images enable...

3DECG-Net: ECG fusion network for multi-label cardiac arrhythmia detection.

Cardiovascular diseases represent the leading global cause of death, typically diagnosed and address...

Fed-CL- an atrial fibrillation prediction system using ECG signals employing federated learning mechanism.

Deep learning has shown great promise in predicting Atrial Fibrillation using ECG signals and other ...

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