Cardiovascular

Atherosclerosis

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

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Reduced order modelling of intracranial aneurysm flow using proper orthogonal decomposition and neural networks.

Reduced order modelling (ROMs) methods, such as proper orthogonal decomposition (POD), systematicall...

Deep learning improves quality of intracranial vessel wall MRI for better characterization of potentially culprit plaques.

Intracranial vessel wall imaging (VWI), which requires both high spatial resolution and high signal-...

Machine learning analysis of serum cholesterol's impact on knee osteoarthritis progression.

The controversy surrounding whether serum total cholesterol is a risk factor for the graded progress...

Advancing aneurysm management: the potential of AI and machine learning in enhancing safety and predictive accuracy.

Cerebral aneurysm rupture, the predominant cause of non-traumatic subarachnoid hemorrhage, underscor...

Predicting Intracranial Aneurysm Rupture: A Multifactor Analysis Combining Radscore, Morphology, and PHASES Parameters.

RATIONALE AND OBJECTIVES: We aimed at developing and validating a nomogram and machine learning (ML)...

Artificial Intelligence and Health Inequities in Dietary Interventions on Atherosclerosis: A Narrative Review.

Poor diet is the top modifiable mortality risk factor globally, accounting for 11 million deaths ann...

Deciphering breast cancer prognosis: a novel machine learning-driven model for vascular mimicry signature prediction.

BACKGROUND: In the ongoing battle against breast cancer, a leading cause of cancer-related mortality...

Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics data.

Integrating multi-omics data into predictive models has the potential to enhance accuracy, which is ...

Development of machine learning models for fractional flow reserve prediction in angiographically intermediate coronary lesions.

BACKGROUND: Fractional flow reserve (FFR) represents the gold standard in guiding the decision to pr...

A comprehensive multi-task deep learning approach for predicting metabolic syndrome with genetic, nutritional, and clinical data.

Metabolic syndrome (MetS) is a complex disorder characterized by a cluster of metabolic abnormalitie...

Revolutionizing Aneurysm detection: The role of artificial intelligence in reducing rupture rates.

Cerebral aneurysms, affecting 2-5% of the global population, are often asymptomatic and commonly loc...

Deep Learning Based Automatic Segmentation of the Thoracic Aorta from Chest Computed Tomography in Healthy Korean Adults.

OBJECTIVE: Segmenting the aorta into zones based on anatomical landmarks is a current trend to bette...

Off-Label use of Woven EndoBridge device for intracranial brain aneurysm treatment: Modeling of occlusion outcome.

INTRODUCTION: The Woven EndoBridge (WEB) device is emerging as a novel therapy for intracranial aneu...

Deep learning for intracranial aneurysm segmentation using CT angiography.

This study aimed to employ a two-stage deep learning method to accurately detect small aneurysms (4-...

A stacking ensemble model for predicting the occurrence of carotid atherosclerosis.

BACKGROUND: Carotid atherosclerosis (CAS) is a significant risk factor for cardio-cerebrovascular ev...

Optimization of Smoking Classification by Applying Neural Network with Variable Importance Using Cytokine Biomarkers.

Cigarette smoking is a preventable epidemic that is a leading cause of death. It increases the risk ...

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