Atherosclerosis

Artificial Intelligence in Neuroradiology: A Review of FDA-regulated Algorithms.

Artificial intelligence (AI) is increasingly integrated into neuroradiology practice, with a growing number of FDA-cleared algorithms now supporting tasks ranging from acute triage to volumetric analysis. This review provides a structured overview of commercially available, FDA-regulated AI tools in neuroradiology, organized by clinical application. These include detection and prioritization of in...

Multi-Omics and Machine Learning Integration Identifies Key Endothelial Modules in Carotid Artery Stenosis.

BACKGROUND: Carotid artery stenosis (CAS) is a major cause of ischemic stroke, yet reliable molecular biomarkers for early identification remain limited. METHODS: We integrated single-cell RNA sequencing (scRNA-seq), bulk transcriptomics, and in-house multi-omics data, applying WGCNA and machine learning to identify endothelial cell-derived diagnostic biomarkers, validated across independent GEO a...

Integrative transcriptomic and single-cell analysis reveals metabolic reprogramming and hexosamine biosynthesis-mediated tumor microenvironment remodeling in prostate cancer.

BACKGROUND: Prostate cancer is one of the most common malignancies in men and exhibits substantial clinical heterogeneity. A considerable proportion o...

Measuring multi-site pulse transit time with an AI-enabled mmWave radar.

Pulse Transit Time (PTT) is a measure of arterial stiffness and a physiological marker associated with cardiovascular function, with an inverse relati...

High-fidelity super-resolution microscopy datasets spanning multispectral to hyperspectral domains via diffractive optics.

Paired datasets are critical for advancing data-driven microscopy but remain scarce for spectral imaging. Here, we present a comprehensive super-resol...

Integrating single-cell and bulk transcriptomic analyses to explore key lactylation-related genes in benign prostatic hyperplasia.

Benign prostatic hyperplasia (BPH) is a prevalent age-related disorder characterized by chronic inflammation, metabolic dysregulation, and abnormal ce...

Identifying potential ligand-receptor interactions by integrating LSTM network and the attention mechanism for cell-cell communication prediction.

BACKGROUND: Cell-cell communication (CCC) mediated by ligand-receptor (L-R) interactions is fundamental to deciphering tissue development and disease ...

Integrative machine learning reveals interplay between epithelial and endothelial cells elevates mixed heavy metal-related colorectal cancer risk.

Heavy metal contamination has become an emerging global health concern, yet the promoting effects of mixed heavy metal exposure on colorectal cancer r...

Bridging discovery and clinical science: A framework for advancing atherosclerosis research using innovative models.

Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of death, with substantial residual risk persisting despite current lipid-lowering, ...

Integrative multi-omics and machine learning reveal glycolysis-related biomarkers driving vascular remodeling in pulmonary arterial hypertension.

Metabolic reprogramming toward aerobic glycolysis, a phenomenon analogous to the Warburg effect, is increasingly recognized as a hallmark of pulmonary...

Optimizing heart failure care: A machine learning-based prediction of hospital length of stay for heart failure patients.

BACKGROUND: Heart failure represents a significant global health burden, with prolonged length of stay (LoS) tied to increased mortality and costs. Ac...

The role of nitrogen dioxide in the prevalence of adverse cardiovascular and cerebrovascular diseases in China: a national multi-pollutant geospatial analysis.

INTRODUCTION: Cardiovascular and cerebrovascular diseases (CCVDs) pose a severe global health threat, particularly among middle-aged and elderly popul...

Attitudes toward artificial intelligence tools in university students: associations with body appreciation and e-healthy diet literacy - implications for digital health education.

BACKGROUND: This cross-sectional study aimed to determine attitudes toward the use of artificial intelligence tools, body appreciation, and e-healthy ...

Machine learning identifies a NETs-related four-gene diagnostic signature for abdominal aortic aneurysm.

Abdominal aortic aneurysm (AAA) is a chronic degenerative disease characterized by localized aortic dilation and persistent inflammation. While neutro...

Biomarker-Guided Strategies for Tumor Vasculature: From Imaging Advances to Novel Therapeutic Interventions.

The tumor vasculature is a dynamic and heterogeneous component of the tumor microenvironment (TME) that influences tumor progression, immune infiltrat...

Disorganization of inner retinal layers and disruption of outer retinal layers as predictors of anti-vascular endothelial growth factor treatment outcomes in diabetic macular edema: A scoping review.

We systematically map the evidence on optical coherence tomography (OCT) biomarkers-mainly disorganization of the retinal inner layers (DRIL), disrupt...

Uric Acid to HDL-C Ratio as a Novel Biomarker for Sarcopenia: A National Study with Machine Learning Insights.

BACKGROUND: Sarcopenia is a major age-related health burden. Although the uric acid to high-density lipoprotein cholesterol ratio (UHR) has been linke...

Predicting intracranial angioplasty failure using vessel wall MRI habitat radiomics and deep learning: a multicenter study.

BACKGROUND: Primary balloon angioplasty (PBA) is a promising strategy for symptomatic intracranial atherosclerotic stenosis but carries the risk of pr...

Machine Learning for Cardiovascular Prevention Prescriptions: Real-World vs. Synthetic Data.

Cardiovascular diseases remain the leading cause of death worldwide, primarily driven by atherosclerosis, which is targeted by lipid-lowering agents s...

Identifying Clinical Predictors of Diabetes and Prediabetes: An Explainable AI Approach Using Primary Care Electronic Medical Records.

Prediabetes (PD), a reversible metabolic condition that precedes type 2 diabetes (T2DM), carries a high risk of progression to T2DM, but can be effect...