Atherosclerosis

Phenotypic clustering of cardiovascular risk profiles in systemic lupus erythematosus.

ObjectiveThis study aimed to identify distinct cardiovascular risk phenotypes in systemic lupus eryt...

Data-driven subgroups for 3-year risk stratification of incident diabetes and complications in diabetes-free Chinese adults.

BACKGROUND: Substantial metabolic heterogeneity exists prior to the development of diabetes, creatin...

Radiomic features and carotid stenosis in periodontitis a two stage bootstrap and multimodal machine learning study.

Bioinformatics approach to identifying molecular targets of Danlou tablet against atherosclerosis: a machine learning pharmacology study.

This research aims to identify novel molecular targets and generate mechanistic hypotheses for Danlo...

Artificial intelligence-powered automatic coronary computed tomography angiography plaque quantification: comparison against optical coherence tomography.

AIMS: Coronary computed tomography angiography (CCTA) enables a non-invasive, comprehensive assessme...

Integrative machine learning identifies a TEAD4-driven endothelial program shaping drug sensitivity and microvascular invasion in HCC.

Environmental bisphenols hijack the Hmox1 and Cdh1 to trigger premature ovarian insufficiency: A multi-omics investigation.

BACKGROUND: Bisphenols A (BPA), bisphenols F (BPF), and bisphenols S (BPS) are environmental endocri...

Deep Learning Reconstruction Combined with Contrast-Enhancement Boost Technique in "Quadruple-low" CCTA Protocol: Evaluation of Image Quality and Diagnostic Accuracy.

RATIONALE AND OBJECTIVES: To evaluate the impact of a deep learning reconstruction (DLR) algorithm c...

Coronary revascularization: a long-term perspective.

This paper will forecast advancements in coronary revascularization by 2040, drawing on historical t...

Redefining Tumor Vascular Permeability through Deep Learning-Guided Microneedle Delivery.

Low-permeability (LP) tumor vasculature constitutes a major barrier to efficient nanomedicine delive...

Modularly-Assembled Smart Microneedle Platform for Machine Learning-Driven Personalized Health Monitoring.

Given the inherent complexity of metabolic pathways and disease-associated agents, next-generation h...

Cardiovascular Risk Assessment Tools in Chronic Kidney Disease.

Cardiovascular (CV) risk calculators estimate the likelihood of CV events by integrating factors suc...

Early Prediction of Adverse Stroke Outcomes using Non-clinical Factors and Missing Data: A Machine Learning Study.

Introduction Early prediction of stroke outcomes using prognostic tools may help clinical decision m...

Enhancing readability and understandability of vascular surgery discharge summaries using artificial intelligence.

ObjectivesThis study aimed to assess whether Large Language Models (LLMs), like ChatGPT-4, could sim...

Effects of Lactiplantibacillus plantarum on moderate dyslipidemia before medication involving gut microbiota and host genetics.

In this 12-week trial, 136 participants with moderately dyslipidemia were randomly assigned to recei...

ANXA2, DBN1, ZNF385D, and IL6ST: Endothelial cell biomarkers linking atherosclerosis progression to immune microenvironment dysregulation.

BACKGROUND: Atherosclerosis (AS) is a complex cardiovascular disorder driven by endothelial cell dys...

Physics-informed graph neural networks for flow field estimation in carotid arteries.

Hemodynamic quantities are valuable biomedical risk factors for cardiovascular pathology such as ath...

Artificial Intelligence-assisted Diagnosis of Carotid Artery Calcifications on Panoramic Radiographs: A Meta-analysis.

Carotid artery calcifications (CACs), a known risk factor for stroke, can be detected on panoramic r...

Commercial AI platforms improve reproducibility but fail to meet clinical precision thresholds for intracranial aneurysm measurement: implications for serial surveillance.

BACKGROUND: Intracranial aneurysm affect 3-7% of the global population, with rupture causing > 80% o...

Development and validation of a computed tomography myocardial perfusion imaging radiomic model for major adverse cardiovascular events prediction: a multicenter study.

AIMS: Accurate prediction of major adverse cardiovascular events (MACE) is crucial for risk stratifi...

Development and validation of interpretable machine learning models for predicting long-term functional outcomes in elderly patients with aneurysmal subarachnoid hemorrhage.

BACKGROUND: Accurate prognostication in elderly patients with aneurysmal subarachnoid hemorrhage (aS...