Cardiovascular

Atherosclerosis

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

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Showing 190-210 of 3,666 articles
A computed tomography angiography-based radiomics model for prognostic prediction of endovascular abdominal aortic repair.

OBJECTIVE: This study aims to develop a radiomics machine learning (ML) model that uses preoperative...

A Novel Mouse Model of Type 2 Diabetes Using a Medium-Fat Diet, Fructose, and Streptozotocin to Study the Complications of Human Disease.

The study of type 2 diabetes mellitus (T2DM) pathophysiology relies mainly on the use of animal mode...

Machine learning analysis of integrated ABP and PPG signals towards early detection of coronary artery disease.

Every year, Coronary Artery Disease (CAD) claims lives of over a million people. CAD occurs when the...

Early prediction of cardiovascular events following treatments in female breast cancer patients: Application of real-world data and artificial intelligence.

• Application of real-world data and artificial intelligence in detecting cardiotoxicity following c...

Elucidating the role of KCTD10 in coronary atherosclerosis: Harnessing bioinformatics and machine learning to advance understanding.

Atherosclerosis (AS) is increasingly recognized as a chronic inflammatory disease that significantly...

Artificial intelligence driven plaque characterization and functional assessment from CCTA using OCT-based automation: A prospective study.

BACKGROUND: We aimed to develop and validate an Artificial Intelligence (AI) model that leverages CC...

Machine Learning Models Integrating Dietary Indicators Improve the Prediction of Progression from Prediabetes to Type 2 Diabetes Mellitus.

: Diet plays an important role in preventing and managing the progression from prediabetes to type 2...

Comparison of Deep Learning and Traditional Machine Learning Models for Predicting Mild Cognitive Impairment Using Plasma Proteomic Biomarkers.

Mild cognitive impairment (MCI) is a clinical condition characterized by a decline in cognitive abil...

Early prediction of postpartum dyslipidemia in gestational diabetes using machine learning models.

This study addresses a gap in research on predictive models for postpartum dyslipidemia in women wit...

Retinal Vascularization Rate Predicts Retinopathy of Prematurity and Remains Unaffected by Low-Dose Bevacizumab Treatment.

PURPOSE: To assess the rate of retinal vascularization derived from ultra-widefield (UWF) imaging-ba...

Using Machine Learning to Predict Outcomes Following Thoracic and Complex Endovascular Aortic Aneurysm Repair.

BACKGROUND: Thoracic endovascular aortic repair (TEVAR) and complex endovascular aneurysm repair (EV...

An interpretable machine learning model with demographic variables and dietary patterns for ASCVD identification: from U.S. NHANES 1999-2018.

Current research on the association between demographic variables and dietary patterns with atherosc...

Modifying the severity and appearance of psoriasis using deep learning to simulate anticipated improvements during treatment.

A neural network was trained to generate synthetic images of severe and moderate psoriatic plaques, ...

Use of deep learning-based high-resolution magnetic resonance to identify intracranial and extracranial symptom-related plaques.

This study aims to develop a deep learning model using high-resolution vessel wall imaging (HR-VWI) ...

Deep learning-based LDL-C level prediction and explainable AI interpretation.

This study investigates the use of deep learning (DL) models to predict low-density lipoprotein chol...

Estimation of Machine Learning-Based Models to Predict Dementia Risk in Patients With Atherosclerotic Cardiovascular Diseases: UK Biobank Study.

BACKGROUND: The atherosclerotic cardiovascular disease (ASCVD) is associated with dementia. However,...

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