Atherosclerosis

Modeling Alzheimer's Disease: From Memory Loss to Plaque & Tangles Formation

We employ the Hopfield model as a simplified framework to explore both the memory deficits and the...

Unsupervised Denoising and Super-Resolution of Vascular Flow Data by Physics-Informed Machine Learning.

We present an unsupervised deep learning method to perform flow denoising and super-resolution witho...

Multimodal ischemic stroke recurrence prediction model based on the capsule neural network and support vector machine.

Ischemic stroke (IS) has a high recurrence rate. Machine learning (ML) models have been developed ba...

Prospective deep learning-based quantitative assessment of coronary plaque by computed tomography angiography compared with intravascular ultrasound: the REVEALPLAQUE study.

AIMS: Coronary computed tomography angiography provides non-invasive assessment of coronary stenosis...

Exploring Prediabetes Pathways Using Explainable AI on Data from Electronic Medical Records.

This study leverages data from a Canadian database of primary care Electronic Medical Records to dev...

Physics-informed graph neural networks for flow field estimation in carotid arteries

Hemodynamic quantities are valuable biomedical risk factors for cardiovascular pathology such as a...

Bioinformatics and machine learning approaches reveal key genes and underlying molecular mechanisms of atherosclerosis: A review.

Atherosclerosis (AS) causes thickening and hardening of the arterial wall due to accumulation of ext...

Machine Learning Constructed Based on Patient Plaque and Clinical Features for Predicting Stent Malapposition: A Retrospective Study.

BACKGROUND: Stent malapposition (SM) following percutaneous coronary intervention (PCI) for myocardi...

Knowledge-Augmented Deep Learning for Segmenting and Detecting Cerebral Aneurysms With CT Angiography: A Multicenter Study.

Background Deep learning (DL) could improve the labor-intensive, challenging processes of diagnosing...

[Deep Learning-Based Artificial Intelligence Model for Automatic Carotid Plaque Identification].

This study aims at developing a dataset for determining the presence of carotid artery plaques in ul...

An efficient pipeline to compute patient-specific cerebral aneurysm wall tension

Cerebral aneurysm rupture, leading to subarachnoid hemorrhage with a high mortality rate, dispropo...

Abdominal aortic aneurysm wall stress: A 7-line code in MATLAB and a one-click software application

An abdominal aortic aneurysm (AAA) is a life-threatening condition characterized by the irreversib...

Prediction of low-density lipoprotein cholesterol levels using machine learning methods.

OBJECTIVE: Low-density lipoprotein cholesterol (LDL-C) has been commonly calculated by equations, bu...

Predicting Diabetes in Canadian Adults Using Machine Learning.

Rising diabetes rates have led to increased healthcare costs and health complications. An estimated ...

Optimizing Coil Selection for Cerebral Aneurysm Treatment Using PyRadiomics and Machine Learning Models.

This study presents an innovative method to increase the accuracy of coil selection for treating cer...

Arterial Diameter Trend Estimation Using Deep Learning on Ultrasound Spectral Doppler.

This study presents an approach for estimating gaps in arterial diameter using flow velocity obtaine...

Deep Learning-Based Estimation of Arterial Stiffness from PPG Spectrograms: A Novel Approach for Non-Invasive Cardiovascular Diagnostics.

Cardiovascular diseases (CVDs), a leading cause of global mortality, are intricately linked to arter...

Classification of Carotid Plaque with Jellyfish Sign Through Convolutional and Recurrent Neural Networks Utilizing Plaque Surface Edges.

In carotid arteries, plaque can develop as localized elevated lesions. The Jellyfish sign, marked by...

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease

\textbf{Objective:} Alzheimer's disease (AD) is the most prevalent form of dementia worldwide, enc...

Revolutionizing aortic aneurysm assessment with artificial intelligence.

Innovative statistical approaches: the use of neural networks reduces the sample size in the splenectomy-MCAO mouse model.

AIM: To compare the effectiveness of artificial neural network (ANN) and traditional statistical ana...