Dyslipidemia

A spatially resolved and lipid-structured model for macrophage populations in early human atherosclerotic lesions

Atherosclerosis is a chronic inflammatory disease of the artery wall. The early stages of atherosclerosis are driven by interactions between lipids and monocyte-derived-macrophages (MDMs). The mechanisms that govern the spatial distribution of lipids and MDMs in the lesion remain poorly understood. In this paper, we develop a spatially-resolved and lipid-structured model for early atherosclerosi...

A machine learning approach for Premature Coronary Artery Disease Diagnosis according to Different Ethnicities in Iran

Premature coronary artery disease (PCAD) refers to the early onset of the disease, usually before the age of 55 for men and 65 for women. Coronary Artery Disease (CAD) develops when coronary arteries, the major blood vessels supplying the heart with blood, oxygen, and nutrients, become clogged or diseased. This is often due to many risk factors, including lifestyle and cardiometabolic ones, but ...

Analysis of TEM micrographs with deep learning reveals APOE genotype-specific associations between HDL particle diameter and Alzheimer's dementia.

High-density lipoprotein (HDL) particle diameter distribution is informative in the diagnosis of many conditions, including Alzheimer's disease (AD). ...

Learning Hemodynamic Scalar Fields on Coronary Artery Meshes: A Benchmark of Geometric Deep Learning Models

Coronary artery disease, caused by the narrowing of coronary vessels due to atherosclerosis, is the leading cause of death worldwide. The diagnostic...

Multi-View Transformers for Airway-To-Lung Ratio Inference on Cardiac CT Scans: The C4R Study

The ratio of airway tree lumen to lung size (ALR), assessed at full inspiration on high resolution full-lung computed tomography (CT), is a major ri...

An Intra- and Cross-frame Topological Consistency Scheme for Semi-supervised Atherosclerotic Coronary Plaque Segmentation

Enhancing the precision of segmenting coronary atherosclerotic plaques from CT Angiography (CTA) images is pivotal for advanced Coronary Atheroscler...

DeepDiff-SHAP: Interpretable deep learning for subgroup-specific causal inference using conditional SHAP

Precision medicine aims to tailor healthcare strategies to individual differences in genetic, clinical, and environmental factors. However, identifyin...

Targeted Enzymatic Fragmentation of Lipoprotein(a) via Kringle IV Domains: A Clearance-Enhancing Therapeutic Strategy for Cardiovascular Disease

Elevated lipoprotein(a) [Lp(a)] is an independent, genetically determined risk factor for atherosclerotic cardiovascular disease (ASCVD). Its unique a...

Hypercholesterolemia Risk Prediction from Serum Metabolomics Using a Metabolic Pathway-Integrated Graph Neural Network

In this paper, we presents a new machine learning framework called the Metabolic Pathway Graph Neural Network (MP-GNN), aimed at predicting hyperchole...

Protocol for the development and validation of machine-learning models for predicting the risk of hypertriglyceridemia in critically ill patients receiving propofol sedation using retrospective data

Propofol is a widely used sedative-hypnotic agent for critically-ill patients requiring invasive mechanical ventilation (IMV). Despite its clinical be...

Predicting Hypertension Among HIV Patients on Antiretroviral Therapy in Rural Eastern Cape, South Africa Using Machine Learning

Hypertension continues to be a major challenge in developing countries like South Africa, as it significantly contributes to the cardiovascular diseas...

Spatially resolved proteomic signatures of atherosclerotic carotid artery disease

Atherosclerotic plaque rupture remains a leading cause of adverse cardiovascular events, yet the molecular drivers of plaque vulnerability are incompl...

Development and validation of a multivariable Prediction Model for Pre-diabetes and Diabetes using Easily Obtainable Clinical Data

In the US, pre-diabetes and diabetes are increasing in prevalence alongside other chronic diseases. Hemoglobin A1c is the most common diagnostic test ...

Modulated smooth muscle cells accumulate late in human coronary atherosclerosis and are temporally and spatially linked to necrotic core formation

Proliferation of arterial smooth muscle cells (SMCs) and their modulation to alternative mesenchymal phenotypes is a central mechanism in the growth o...

Demonstrating the potential of untargeted hair proteomics for personalized biomarkers in stress-associated disorders

Biomarker research in psychopathology increasingly employs high-dimensional omics approaches. Yet, proteomics based on human hair remain largely unexp...

Intraplaque haemorrhage quantification and molecular characterisation using attention based multiple instance learning

Intraplaque haemorrhage (IPH) represents a critical feature of plaque vulnerability as it is robustly associated with adverse cardiovascular events, i...

Clinical phenotypes in hypertension: a data-driven approach to risk stratification and outcome prediction

Hypertension (HTN) is a major contributor to cardiovascular (CV) morbidity and mortality. Its heterogeneity complicates risk stratification. Unsupervi...

Extracting Carotid Stenosis Severity from Clinical Notes Using Natural Language Processing: Development, Validation, and Application in a Nationwide Veteran Cohort

Carotid stenosis, which is atherosclerotic narrowing of the extracranial carotid arteries, is an important risk factor for ischemic stroke. The preval...

Machine learning models for the prediction of COVID-19 prognosis in the primary health care setting

This study aimed to identify prognostic factors associated with poor outcomes of COVID-19 at diagnosis in Primary Health Care (PHC). We conducted a re...

Kolmogorov-Arnold Network for Atherosclerotic Cardiovascular Disease Risk Prediction

Assessing the risk of future atherosclerotic cardiovascular disease (ASCVD) is crucial in clinical practice, yet it continues to pose significant chal...