Cardiovascular

Atherosclerosis

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

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Machine Learning Identification of Nutrient Intake Variations across Age Groups in Metabolic Syndrome and Healthy Populations.

This study undertakes a comprehensive examination of the intricate link between diet nutrition, age,...

Artificial Intelligence in Cardiovascular Disease Prevention: Is it Ready for Prime Time?

PURPOSE OF REVIEW: This review evaluates how Artificial Intelligence (AI) enhances atherosclerotic c...

A new machine learning model to predict the prognosis of cardiogenic brain infarction.

Cardiogenic cerebral infarction (CCI) is a disease in which the blood supply to the blood vessels in...

Identifying Cardiovascular Disease Risk Endotypes of Adolescent Major Depressive Disorder Using Exploratory Unsupervised Machine Learning.

OBJECTIVE: Adolescents with major depressive disorder (MDD) are at increased risk of premature ather...

Artificial Intelligence-Enabled Quantitative Coronary Plaque and Hemodynamic Analysis for Predicting Acute Coronary Syndrome.

BACKGROUND: A lesion-level risk prediction for acute coronary syndrome (ACS) needs better characteri...

Use of Artificial Intelligence Software to Detect Intracranial Aneurysms: A Comprehensive Stroke Center Experience.

OBJECTIVE: To evaluate variability in aneurysm detection and the potential of artificial intelligenc...

Branched Convolutional Neural Networks for Receiver Channel Recovery in High-Frame-Rate Sparse-Array Ultrasound Imaging.

For high-frame-rate ultrasound imaging, it remains challenging to implement on compact systems as a ...

Risk prediction model of metabolic syndrome in perimenopausal women based on machine learning.

INTRODUCTION: Metabolic syndrome (MetS) is considered to be an important parameter of cardio-metabol...

Development and multinational validation of an algorithmic strategy for high Lp(a) screening.

Elevated lipoprotein (a) (Lp(a)) is associated with premature atherosclerotic cardiovascular disease...

Deep learning-based fully automatic screening of carotid artery plaques in computed tomography angiography: a multicenter study.

AIM: To develop and validate a deep learning (DL) algorithm for the automated detection and classifi...

Radiomics and artificial intelligence: General notions and applications in the carotid vulnerable plaque.

Carotid atherosclerosis plays a substantial role in cardiovascular morbidity and mortality. Given th...

Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes.

Almost 35 years after its introduction, coronary artery calcium score (CACS) not only survived techn...

Cryo-EM images of phase-separated lipid bilayer vesicles analyzed with a machine-learning approach.

Lateral lipid heterogeneity (i.e., raft formation) in biomembranes plays a functional role in living...

A Deep Learning Framework for Analysis of the Eustachian Tube and the Internal Carotid Artery.

OBJECTIVE: Obtaining automated, objective 3-dimensional (3D) models of the Eustachian tube (ET) and ...

Prediction and causal inference of hyperuricemia using gut microbiota.

Hyperuricemia (HUA) is a symptom of high blood uric acid (UA) levels, which causes disorders such as...

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

The quantification of carotid plaque has been routinely used to predict cardiovascular risk in cardi...

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

ObjectivesAssessment of plaque stenosis severity allows better management of carotid source of strok...

Progression from Prediabetes to Diabetes in a Diverse U.S. Population: A Machine Learning Model.

To date, there are no widely implemented machine learning (ML) models that predict progression from...

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