Cardiovascular

Dyslipidemia

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

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Identification of the Best Anthropometric Predictors of Serum High- and Low-Density Lipoproteins Using Machine Learning.

Serum high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol levels are associ...

Early Identification of Vitamin D Deficiency Risk Through Public Health Screening Data.

Metabolic syndrome, characterized by central obesity, hypertension, hyperglycemia, dyslipidemia, and...

Automate Creating, Customizing, and Optimizing Comorbidity Indices Using a Data-Driven AI/ML Approach.

Due to individual differences in severity of illness, clinical studies typically use a comorbidity i...

Associations of the Hs-CRP/HDL-C ratio with stroke among US adults: Evidence from NHANES 2015-2018.

BACKGROUND: The high-sensitivity C-reactive protein (Hs-CRP)-to-high-density lipoprotein cholesterol...

Discovery of novel potential 11β-HSD1 inhibitors through combining deep learning, molecular modeling, and bio-evaluation.

11β-Hydroxysteroid dehydrogenase type 1 (11β-HSD1) has been shown to play an important role in the t...

Advances in the application of 18 F-sodium fluoride PET in the assessment of atherosclerosis.

Atherosclerosis serves as the primary cause of cardiovascular diseases (CVDs), with its pathological...

Computed Tomography Advancements in Plaque Analysis: From Histology to Comprehensive Plaque Burden Assessment.

Advancements in coronary computed tomography angiography (CCTA) facilitated the transition from trad...

Recommendations for the Management of Diabetes During Ramadan Applying the Principles of the ADA/ EASD Consensus: Update 2025.

Ramadan fasting is a sacred ritual observed by approximately 1.8 billion Muslims each year, most of ...

A flexible machine learning Mendelian randomization estimator applied to predict the safety and efficacy of sclerostin inhibition.

Mendelian randomization (MR) enables the estimation of causal effects while controlling for unmeasur...

Assessing the Global Impact of Brain Small Vessel Disease on Cognition: The Multi-Ethnic Study of Atherosclerosis.

INTRODUCTION: We aimed to examine the global impact of brain small vessel disease (SVD) on cognitive...

PET imaging of atherosclerosis: artificial intelligence applications and recent advancements.

PET imaging has become a valuable tool for assessing atherosclerosis by targeting key processes such...

Elucidating the role of KLRD1 in coronary atherosclerosis: harnessing bioinformatics and machine learning to advance understanding.

BACKGROUND: Atherosclerosis (AS) is increasingly recognized as a chronic inflammatory disease that s...

The role of mitochondrial dysfunction in the pathogenesis of atherosclerosis: A new exploration from bioinformatics analysis.

Atherosclerosis (AS) is a complex cardiovascular disease associated with mitochondrial dysfunction (...

Predictive factors of hypoglycemia in type 2 diabetes: a prospective study using machine learning.

Hypoglycemia is a serious complication in individuals with type 2 diabetes mellitus. Identifying who...

Predicting cardiovascular risk with hybrid ensemble learning and explainable AI.

Cardiovascular diseases (CVDs) are still one of the leading causes of death globally, underscoring t...

Machine learning using scRNA-seq Combined with bulk-seq to identify lactylation-related hub genes in carotid arteriosclerosis.

Atherosclerosis is a chronic inflammatory disease, this study aims to investigate the immune landsca...

Recognizing artery segments on carotid ultrasonography using embedding concatenation of deep image and vision-language models.

Evaluating large artery atherosclerosis is critical for predicting and preventing ischemic strokes. ...

Diagnostic value of small dense low-density lipoprotein and trace elements in coronary artery disease.

Coronary artery disease (CAD) is a worldwide leading cause of death. Considering that 20%-40% of pat...

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