Cardiovascular

Dyslipidemia

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

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Showing 904-924 of 4,006 articles
Comparison of the Expert Guidelines With Artificial Intelligence-Driven Echocardiographic Assessment of Diastolic Function

Backgound: Accurate assessment of diastolic function and left ventricular (LV) filling pressure is c...

Liver Biomarker Improves AHA/ACC 10-year ASCVD Risk Prediction in US and China Cohorts with ML

Introduction: Accurate stratification of hard atherosclerotic cardiovascular disease (ASCVD) risk re...

Cardiometabolic health trajectories from birth to old age based on multi-decadal series of biochemistry and anthropometry

Background and aims: Direct evidence to connect early life metabolism with cardiometabolic diseases ...

When AI Shows Its Work, Is It Actually Working? Step-Level Evaluation Reveals Frontier Language Models Frequently Bypass Their Own Reasoning

Language models increasingly "show their work" by writing step-by-step reasoning before answering. B...

CARDIAC-FM: A Multimodal Foundation Model for Cardiovascular Risk Prediction Using ECG and Cardiac MRI

Atrial fibrillation and heart failure impose substantial health burdens worldwide, yet existing pred...

Longitudinal immune transcriptomic signatures are associated with carotid intima-media thickness over 18 years

Background. Atherosclerosis is increasingly recognized as a chronic immunometabolic disorder involvi...

Phenotypic reversion and target prioritization for cellular inflammation via representation learning with foundation models

The identification of genetic perturbations that can reverse disease-associated cellular phenotypes ...

MRI Contrast Enhancement Kinetics World Model

Clinical MRI contrast acquisition suffers from inefficient information yield, which presents as a mi...

AI-Detected Asymptomatic Atrial Fibrillation and Risk of Incident Ischemic Stroke and Cardiovascular Events: A UK Biobank Study

Background: Advances in wearable devices and machine-learning-based ECG analysis enable highly accur...

Spatial multi-omics identify an immunosuppressive lipid-laden macrophage niche in primary CNS lymphoma

Primary central nervous system lymphoma (PCNSL) is a subtype of diffuse large B-cell lymphoma (DLBCL...

Insulin resistance modifies longitudinal multi-omics responses to habitual diet

How habitual diet influences the gut microbiome and plasma metabolome across insulin resistance stat...

ESUS-AI:a machine learning framework to estimate the most likely embolic source in embolic stroke of undetermined source

Background and Purpose Embolic stroke of undetermined source (ESUS) emains a major diagnostic challe...

NIMETOX-informed Precision Nomothetic Models of Major Depressive Disorder: Group, Phenome, and Individual Signatures

Background: Major depressive disorder (MDD) is a neuro-immune-metabolic-oxidative (NIMETOX) disorder...

Development and Multinational Validation of Artificial Intelligence-Enabled ASCVD Risk Stratification Using Electrocardiograms

Aims: Despite the availability of clinical risk scores for atherosclerotic cardiovascular disease (A...

A genotype-phenotype transformer to assess and explain polygenic risk

Genome-wide association studies have linked millions of genetic variants to biomedical phenotypes, b...

Semi-supervised learning and integration of multi-sequence MR-images for carotid vessel wall and plaque segmentation

The analysis of carotid arteries, particularly plaques, in multi-sequence Magnetic Resonance Imagi...

Atherosclerosis through Hierarchical Explainable Neural Network Analysis

In this work, we study the problem pertaining to personalized classification of subclinical athero...

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