Cardiovascular

Dyslipidemia

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

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Can small dense LDL cholesterol be estimated from the lipid profile?

PURPOSE OF REVIEW: Small dense low-density lipoprotein cholesterol (sdLDL-C) is recognized for its s...

The Influence of an AI-Driven Personalized Nutrition Program on the Human Gut Microbiome and Its Health Implications.

Personalized nutrition programs enhanced with artificial intelligence (AI)-based tools hold promisi...

Gender Differences in Predicting Metabolic Syndrome Among Hospital Employees Using Machine Learning Models: A Population-Based Study.

BACKGROUND: Metabolic syndrome (MetS) is a complex condition that captures several markers of dysreg...

AI-Quantitative CT Coronary Plaque Features Associate With a Higher Relative Risk in Women: CONFIRM2 Registry.

BACKGROUND: Coronary plaque features are imaging biomarkers of cardiovascular risk, but less is know...

Comparing machine learning models for osteoporosis prediction in Tibetan middle aged and elderly women.

The aim of this study was to establish the optimal prediction model by comparing the prediction effe...

Role of physics-informed constraints in real-time estimation of 3D vascular fluid dynamics using multi-case neural network.

Numerical simulations of fluid dynamics in tube-like structures are important to biomedical research...

Nutritional predictors of lymphatic filariasis progression: Insights from a machine learning approach.

Lymphatic filariasis (LF) is a mosquito-borne neglected tropical disease that causes disfiguring of ...

Machine learning reveals distinct neuroanatomical signatures of cardiovascular and metabolic diseases in cognitively unimpaired individuals.

Comorbid cardiovascular and metabolic risk factors (CVM) differentially impact brain structure and i...

Machine learning for predicting metabolic-associated fatty liver disease including NHHR: a cross-sectional NHANES study.

OBJECTIVE: Metabolic - associated fatty liver disease (MAFLD) is a common hepatic disorder with incr...

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...

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...

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...

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...

Spatial analysis of air pollutant exposure and its association with metabolic diseases using machine learning.

BACKGROUND: Metabolic diseases (MDs), exemplified by diabetes, hypertension, and dyslipidemia, have ...

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