Cardiovascular

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

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End-to-end deep-learning model for the detection of coronary artery stenosis on coronary CT images.

PURPOSE: We examined whether end-to-end deep-learning models could detect moderate (≥50%) or severe ...

A python approach for prediction of physicochemical properties of anti-arrhythmia drugs using topological descriptors.

In recent years, machine learning has gained substantial attention for its ability to predict comple...

Integrating CNN and Bi-LSTM for protein succinylation sites prediction based on Natural Language Processing technique.

Protein succinylation, a post-translational modification wherein a succinyl group (-CO-CHâ‚‚-CHâ‚‚-CO-) ...

TinyML and edge intelligence applications in cardiovascular disease: A survey.

Tiny machine learning (TinyML) and edge intelligence have emerged as pivotal paradigms for enabling ...

Bioinspired Smart Triboelectric Soft Pneumatic Actuator-Enabled Hand Rehabilitation Robot.

Quantitative assessment for post-stroke spasticity remains a significant challenge due to the encoun...

Automated classification of coronary LEsions fRom coronary computed Tomography angiography scans with an updated deep learning model: ALERT study.

OBJECTIVES: The use of deep learning models for quantitative measurements on coronary computed tomog...

Residual-attention deep learning model for atrial fibrillation detection from Holter recordings.

BACKGROUND: Detecting subtle patterns of atrial fibrillation (AF) and irregularities in Holter recor...

Cardiac MR image reconstruction using cascaded hybrid dual domain deep learning framework.

Recovering diagnostic-quality cardiac MR images from highly under-sampled data is a current research...

Artificial intelligence-based framework for early detection of heart disease using enhanced multilayer perceptron.

Cardiac disease refers to diseases that affect the heart such as coronary artery diseases, arrhythmi...

Machine Learning Approach for Sepsis Risk Assessment in Ischemic Stroke Patients.

BackgroundIschemic stroke is a critical neurological condition, with infection representing a signif...

Automated stenosis estimation of coronary angiographies using end-to-end learning.

The initial evaluation of stenosis during coronary angiography is typically performed by visual asse...

Prediction of Aneurysm Sac Shrinkage After Endovascular Aortic Repair Using Machine Learning-Based Decision Tree Analysis.

INTRODUCTION: A simple risk stratification model to predict aneurysm sac shrinkagein patients underg...

Predicting mortality after transcatheter aortic valve replacement using AI-based fully automated left atrioventricular coupling index.

BACKGROUND: This study aimed to determine whether artificial intelligence (AI)-based automated asses...

Enhancing stroke disease classification through machine learning models via a novel voting system by feature selection techniques.

Heart disease remains a leading cause of mortality and morbidity worldwide, necessitating the develo...

Prediction of delirium occurrence using machine learning in acute stroke patients in intensive care unit.

INTRODUCTION: Delirium, frequently experienced by ischemic stroke patients, is one of the most commo...

single nucleotide polymorphism reduces dabigatran acylglucuronide formation in humans.

BACKGROUND: Dabigatran etexilate (DABE), a prodrug of dabigatran (DAB), is a direct thrombin inhibit...

Machine learning-based analyses of contributing factors for the development of hypertension: a comparative study.

OBJECTIVES: Sufficient attention has not been given to machine learning (ML) models using longitudin...

Repeatability of AI-based, automatic measurement of vertebral and cardiovascular imaging biomarkers in low-dose chest CT: the ImaLife cohort.

OBJECTIVE: To evaluate the repeatability of AI-based automatic measurement of vertebral and cardiova...

Deep learning model to identify and validate hypotension endotypes in surgical and critically ill patients.

BACKGROUND: Hypotension is associated with organ injury and death in surgical and critically ill pat...

Clustering-based binary Grey Wolf Optimisation model with 6LDCNNet for prediction of heart disease using patient data.

In recent years, the healthcare data system has expanded rapidly, allowing for the identification of...

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