AIMC Topic: Carotid Intima-Media Thickness

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Sex-specific machine learning models for carotid plaque prediction in individuals with fatty liver disease: a cross-sectional study.

BMJ open
INTRODUCTION: Early detection of carotid plaque prevents stroke and myocardial infarction. Individuals with fatty liver might be at an increased risk of developing carotid plaque, yet limited access to carotid artery ultrasound underscores the need f...

Beyond unimodal analysis: Multimodal ensemble learning for enhanced assessment of atherosclerotic disease progression.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Atherosclerosis is a leading cardiovascular disease typified by fatty streaks accumulating within arterial walls, culminating in potential plaque ruptures and subsequent strokes. Existing clinical risk scores, such as systematic coronary risk estimat...

Enhanced stroke risk prediction in hypertensive patients through deep learning integration of imaging and clinical data.

BMC medical informatics and decision making
BACKGROUND: Stroke is one of the leading causes of death and disability worldwide, with a significantly elevated incidence among individuals with hypertension. Conventional risk assessment methods primarily rely on a limited set of clinical parameter...

Artificial intelligence-based cardiovascular/stroke risk stratification in women affected by autoimmune disorders: a narrative survey.

Rheumatology international
Women are disproportionately affected by chronic autoimmune diseases (AD) like systemic lupus erythematosus (SLE), scleroderma, rheumatoid arthritis (RA), and Sjögren's syndrome. Traditional evaluations often underestimate the associated cardiovascul...

Deep learning approach for cardiovascular disease risk stratification and survival analysis on a Canadian cohort.

The international journal of cardiovascular imaging
The quantification of carotid plaque has been routinely used to predict cardiovascular risk in cardiovascular disease (CVD) and coronary artery disease (CAD). To determine how well carotid plaque features predict the likelihood of CAD and cardiovascu...

A deep learning-based calculation system for plaque stenosis severity on common carotid artery of ultrasound images.

Vascular
ObjectivesAssessment of plaque stenosis severity allows better management of carotid source of stroke. Our objective is to create a deep learning (DL) model to segment carotid intima-media thickness and plaque and further automatically calculate plaq...

A Siamese ResNeXt network for predicting carotid intimal thickness of patients with T2DM from fundus images.

Frontiers in endocrinology
OBJECTIVE: To develop and validate an artificial intelligence diagnostic model based on fundus images for predicting Carotid Intima-Media Thickness (CIMT) in individuals with Type 2 Diabetes Mellitus (T2DM).

Emerging Feature Extraction Techniques for Machine Learning-Based Classification of Carotid Artery Ultrasound Images.

Computational intelligence and neuroscience
Plaque deposits in the carotid artery are the major cause of stroke and atherosclerosis. Ultrasound imaging is used as an early indicator of disease progression. Classification of the images to identify plaque presence and intima-media thickness (IMT...

Vitamin D insufficiency is associated with subclinical atherosclerosis in HIV-1-infected patients on combination antiretroviral therapy.

HIV research & clinical practice
Vitamin D insufficiency has been associated with faster progression of atherosclerosis and increased cardiovascular disease risk, but limited data are available in HIV-infected people. So, we examined potential correlation between vitamin D status a...

Semantic segmentation with DenseNets for carotid artery ultrasound plaque segmentation and CIMT estimation.

Artificial intelligence in medicine
BACKGROUND AND OBJECTIVE: The measurement of carotid intima media thickness (CIMT) in ultrasound images can be used to detect the presence of atherosclerotic plaques. Usually, the CIMT estimation strategy is semi-automatic, since it requires: (1) a m...