Atherosclerosis

Lesion-Specific Prediction of Segmental Fractional Flow Reserve Using Deep Learning and Optical Coherence Tomography-Derived Features.

BACKGROUND: Intracoronary imaging-derived physiologic indices enable vessel-level assessment of coronary flow impairment by integrating obstructive plaque burden. However, accurately evaluating hyperemic flow remains challenging due to the difficulty of simultaneously incorporating both vascular geometry and plaque composition. METHODS AND RESULTS: We aimed to develop and validate a deep learning ...

Machine learning-based prediction of hepatocellular carcinoma risk in steatotic liver disease: A nationwide cohort study.

BACKGROUND AND AIMS: Steatotic liver disease (SLD) has emerged as an important risk factor for hepatocellular carcinoma (HCC), often in the absence of cirrhosis. We aimed to develop explainable machine learning (ML) models to predict HCC risk in individuals with SLD using routinely collected screening data. METHODS: Using the Korean National Health Insurance Service database, we included adults ag...

Peripheral immune and vascular inflammatory signatures precede Alzheimer's disease onset: A serum proteomic study.

BackgroundNeuroinflammation plays an important role in the pathogenesis of Alzheimer's disease, but systemic immune alterations preceding clinical ons...

Genome-Wide Association Study and Fine Mapping Uncover Key Genetic Loci and Credible Genes of Intracranial Aneurysm and Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND: Intracranial aneurysm (IA) is a common neurovascular disorder; rupture causes aneurysmal subarachnoid hemorrhage with high mortality. Desp...

Angioarchitectural features of hemorrhagic presentation of brain arteriovenous malformations: A multivariate and explainable machine learning study.

PURPOSE: Brain arteriovenous malformations (BAVM) pose a significant rupture risk, leading to morbidity and mortality. Identifying features associated...

Voice-assisted artificial intelligence in cardiovascular disease management: a systematic review and meta-analysis protocol.

INTRODUCTION: Cardiovascular disease (CVD) remains a leading cause of global morbidity and mortality, with self-management playing a pivotal role in i...

Stage-Associated Subgingival Dysbiosis Across the Periodontal Disease Spectrum in a Thai Cohort.

AIMS: This cross-sectional study aimed to investigate the subgingival microbiota and predict functional profiles across the 2018 EFP/AAP periodontal d...

Integrating Structural and Functional Ultrasound Carotid Assessment in a Single Software Platform: Development and Feasibility Evaluation.

BACKGROUND: The extensive assessment of vascular health requires the integration of both structural and functional (hemodynamic) parameters. These are...

Association of triglyceride-cholesterol-body weight index with in-hospital mortality in critically ill patients with heart failure.

Malnutrition and metabolic abnormalities are common in patients with heart failure (HF) requiring intensive care unit (ICU) admission and are associat...

Wherever, Whenever, and However It Is Found: Atherosclerosis Is Informative.

Beyond the Coronaries: Utility of Extra-Coronary Calcification for Cardiovascular Risk Assessment in Women.

PURPOSE OF REVIEW: Globally, cardiovascular disease (CVD) is the leading cause of mortality in women. Traditional risk calculators underestimate ather...

Diagnostic Performance of General Practitioners in Carotid Plaque Detection Using AI-Enhanced Point-of-Care Ultrasound After Systematic Training.

PURPOSE: While point-of-care ultrasound (POCUS) has been integrated into daily practice by general practitioners (GPs) in some countries, there is a p...

Advanced Quantitative CT for Coronary Artery Disease: Integrating Stenosis-, Plaque Quantification, and FFR-CT.

Coronary artery disease (CAD) continues to be a leading cause of death globally. Radiological evaluation of CAD generally consists of stenosis detecti...

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 t...

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 limit...

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 ...