Cardiovascular

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

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Showing 2395-2415 of 9,252 articles
Automated inversion time selection for late gadolinium-enhanced cardiac magnetic resonance imaging.

OBJECTIVES: To develop and share a deep learning method that can accurately identify optimal inversi...

A comprehensive and reliable feature attribution method: Double-sided remove and reconstruct (DoRaR).

The limited transparency of the inner decision-making mechanism in deep neural networks (DNN) and ot...

Mitral Valve Segmentation and Tracking from Transthoracic Echocardiography Using Deep Learning.

OBJECTIVE: Valvular heart diseases (VHDs) pose a significant public health burden, and deciding the ...

Transforming clinical cardiology through neural networks and deep learning: A guide for clinicians.

The rapid evolution of neural networks and deep learning has revolutionized various fields, with cli...

Improving deep-learning electrocardiogram classification with an effective coloring method.

Cardiovascular diseases, particularly arrhythmias, remain a leading cause of mortality worldwide. El...

An artificial intelligence based abdominal aortic aneurysm prognosis classifier to predict patient outcomes.

Abdominal aortic aneurysms (AAA) have been rigorously investigated to understand when their clinical...

Deep Learning for Chest X-ray Diagnosis: Competition Between Radiologists with or Without Artificial Intelligence Assistance.

This study aimed to assess the performance of a deep learning algorithm in helping radiologist achie...

Enhancing diagnostic deep learning via self-supervised pretraining on large-scale, unlabeled non-medical images.

BACKGROUND: Pretraining labeled datasets, like ImageNet, have become a technical standard in advance...

Inadequate Anti-Factor Xa Levels With Daily 40-mg Enoxaparin After Cardiac Surgery.

BACKGROUND: Cardiac surgery patients are at increased risk for venous thromboembolism (VTE). Prevent...

The Role of Artificial Intelligence in Cardiac Imaging.

Artificial intelligence (AI) is having a significant impact in medical imaging, advancing almost eve...

Continuous Atrial Fibrillation Monitoring From Photoplethysmography: Comparison Between Supervised Deep Learning and Heuristic Signal Processing.

BACKGROUND: Continuous monitoring for atrial fibrillation (AF) using photoplethysmography (PPG) from...

Pediatric ECG-Based Deep Learning to Predict Left Ventricular Dysfunction and Remodeling.

BACKGROUND: Artificial intelligence-enhanced ECG analysis shows promise to detect ventricular dysfun...

Identification of Atrial Fibrillation With Single-Lead Mobile ECG During Normal Sinus Rhythm Using Deep Learning.

BACKGROUND: The acquisition of single-lead electrocardiogram (ECG) from mobile devices offers a more...

Attention-Based Deep Learning Model for Prediction of Major Adverse Cardiovascular Events in Peritoneal Dialysis Patients.

Major adverse cardiovascular events (MACE) encompass pivotal cardiovascular outcomes such as myocard...

Snippet Policy Network V2: Knee-Guided Neuroevolution for Multi-Lead ECG Early Classification.

Early time series classification predicts the class label of a given time series before it is comple...

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