Cardiovascular

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

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Using Machine Learning to Predict the Duration of Atrial Fibrillation: Model Development and Validation.

BACKGROUND: Atrial fibrillation (AF) is a progressive disease, and its clinical type is classified a...

Machine Learning-Based Prediction of Death and Hospitalization in Patients With Implantable Cardioverter Defibrillators.

BACKGROUND: Predicting the clinical trajectory of individual patients with implantable cardioverter-...

Artificial intelligence-driven intelligent learning models for identification and prediction of cardioneurological disorders: A comprehensive study.

The integration of Artificial Intelligence (AI) and Intelligent Learning Models (ILMs) in healthcare...

Prediction of Survival After Pediatric Cardiac Arrest Using Quantitative EEG and Machine Learning Techniques.

BACKGROUND AND OBJECTIVES: Early neuroprognostication in children with reduced consciousness after c...

Enhancing Motor Imagery Classification with Residual Graph Convolutional Networks and Multi-Feature Fusion.

Stroke, an abrupt cerebrovascular ailment resulting in brain tissue damage, has prompted the adoptio...

CIS-UNet: Multi-class segmentation of the aorta in computed tomography angiography via context-aware shifted window self-attention.

Advancements in medical imaging and endovascular grafting have facilitated minimally invasive treatm...

A machine learning prediction model for Cardiac Amyloidosis using routine blood tests in patients with left ventricular hypertrophy.

Current approaches for cardiac amyloidosis (CA) identification are time-consuming, labor-intensive, ...

Machine Learning Identifies Clinically Distinct Phenotypes in Patients With Aortic Regurgitation.

BACKGROUND: Aortic regurgitation (AR) is a prevalent valve disease with a long latent period before ...

Machine learning for stroke in heart failure with reduced ejection fraction but without atrial fibrillation: A post-hoc analysis of the WARCEF trial.

BACKGROUND: The prediction of ischaemic stroke in patients with heart failure with reduced ejection ...

Exploratory analysis of Type B Aortic Dissection (TBAD) segmentation in 2D CTA images using various kernels.

Type-B Aortic Dissection is a rare but fatal cardiovascular disease characterized by a tear in the i...

Prediction and Elimination of Physiological Tremor During Control of Teleoperated Robot Based on Deep Learning.

Currently, teleoperated robots, with the operator's input, can fully perceive unknown factors in a c...

Foot fractures diagnosis using a deep convolutional neural network optimized by extreme learning machine and enhanced snow ablation optimizer.

The current investigation proposes a novel hybrid methodology for the diagnosis of the foot fracture...

Optimizing early diagnosis by integrating multiple classifiers for predicting brain stroke and critical diseases.

Machine learning has gained attention in the medical field. Continuous efforts are being made to dev...

Accuracy of Machine Learning in Discriminating Kawasaki Disease and Other Febrile Illnesses: Systematic Review and Meta-Analysis.

BACKGROUND: Kawasaki disease (KD) is an acute pediatric vasculitis that can lead to coronary artery ...

An interpretable machine learning scoring tool for estimating time to recurrence readmissions in stroke patients.

BACKGROUND: Stroke recurrence readmission poses an additional burden on both patients and healthcare...

Natural Language Processing to Adjudicate Heart Failure Hospitalizations in Global Clinical Trials.

BACKGROUND: Medical record review by a physician clinical events committee is the gold standard for ...

Impact of tooth loss and patient characteristics on coronary artery calcium score classification and prediction.

This study, for the first time, explores the integration of data science and machine learning for th...

Machine learning for predicting in-hospital mortality in elderly patients with heart failure combined with hypertension: a multicenter retrospective study.

BACKGROUND: Heart failure combined with hypertension is a major contributor for elderly patients (≥ ...

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