Peripheral Artery Disease

Sex differences in microvascular patterns associated with low- and high-risk for cardiovascular disease.

BACKGROUND: The role of the microcirculation in cardiovascular health in males and females is not fully understood. Skin microvascular function can be assessed non-invasively by measuring the response to a brief occlusion of the arm, which produces a hyperemic response that depends on multiple regulatory pathways. Whether the resulting time-resolved microvascular parameters discriminate between lo...

Leveraging free-text clinical records for heart disease classification through structured feature mapping.

Hypertension and diabetes are major risk factors for heart disease, which remains among the leading causes of morbidity and mortality worldwide. Heart disease includes heart failure, myocardial infarction, stroke, and atherosclerosis. The identification and monitoring of these risk factors are crucial for early intervention and effective management. Machine learning techniques have the potential t...

Risk Factors for Coronary Heart Disease and Stroke Among Older Adults With Metabolic Dysfunction-Associated Steatotic Liver Disease: A Nationwide Cohort Study.

BACKGROUND: Older adults with metabolic dysfunction-associated steatotic liver disease have elevated cardiovascular disease (CVD) risk, yet convention...

Machine learning-based identification of cardiovascular risk modifiers in patients with very high LDL cholesterol: A cross-sectional study.

Individuals with LDL cholesterol (LDL-C) ≥ 190 mg/dL face a markedly increased risk of major adverse cardiovascular events (MACE). Traditional risk ca...

AI-based Synthetic CT Angiography from Non-contrast CT for Cerebrovascular Disease Screening.

BACKGROUND: CT angiography (CTA) is a key investigation in cerebrovascular disease. However, CTA is not always available and it also requires intraven...

Machine learning-based clinical models for prediction of urinary incontinence after robot-assisted laparoscopic radical prostatectomy.

OBJECTIVE: To investigate risk factors for urinary incontinence (UI) after robot-assisted laparoscopic radical prostatectomy (RARP) using interpretabl...

FOXC1: A Key Transcription Factor of VSMC-Derived Foam Cell Formation in Atherosclerotic Plaque Instability.

The instability of atherosclerotic plaques, particularly intraplaque hemorrhage (IPH), drives life-threatening cardiovascular events, a process in whi...

[Overview and conclusions of the STROKE data platform of the National Laboratory for Translational Neuroscience and the associated clinical studies].

Acute ischemic and hemorrhagic stroke are among the leading causes of mortality and long-term disability worldwide. In addition to the results of rand...

Developing machine learning models to improve cardiovascular risk prediction for people living with HIV.

BACKGROUND: As life expectancy rises for people with HIV, atherosclerotic cardiovascular disease (ASCVD) has become a major contributor to morbidity. ...

The Spanish Atherosclerosis Society Dyslipidaemia Registry: Evolution, real-world evidence, and its role in precision medicine. Current status in 2026.

INTRODUCTION: The National Dyslipidemia Registry of the Spanish Atherosclerosis Society (SEA) represents a major source of real-world evidence on lipi...

Optimizing coronary artery disease management: the role of CT-derived fractional flow reserve in predicting revascularization and guiding clinical decisions.

OBJECTIVE: Coronary artery disease (CAD) is the most common heart disease, and invasive coronary angiography (ICA) has been recognized as the gold sta...

A novel dynamic Optuna hybrid Harris Hawks Optimization approach for classification of CAD.

Coronary Artery Disease (CAD) is a leading cause of mortality worldwide and is primarily associated with atherosclerotic plaque formation, resulting i...

Incremental prognostic value of AI-based coronary CT angiography combined with PET/CT dynamic myocardial perfusion imaging in patients with suspected or confirmed coronary artery disease.

BACKGROUND: Coronary computed tomography angiography (CCTA) and positron emission tomography/computed tomography (PET/CT) myocardial perfusion imaging...

Bioinformatics identification of candidate biomarkers associated with T cell proliferation in atherosclerosis via WGCNA and machine learning.

BACKGROUND: Atherosclerosis (AS) is a complex chronic disease caused by the development of atherosclerotic plaques. T cell proliferation exerts a vita...

Natural language processing identifies symptoms predicting complete coronary artery occlusion in patients with NSTEMI.

AIMS: One in 10 patients present to the emergency department (ED) with symptoms of acute coronary syndrome (ACS). The 13-item ACS Symptom Checklist is...

Automated deep learning-based arousal detection complies with ten expert scorers in unseen data.

STUDY OBJECTIVES: Automatic arousal scoring is essential for the cost-effective analysis of polysomnograms. Many previous automatic methods have been ...

Machine Learning Analysis of Sex Differences in Cardiovascular-Kidney-Metabolic Risk Factors and Prognosis Among Patients With Moderate-to-Severe Coronary Artery Calcification: Prospective Cohort Study.

BACKGROUND: Patients with coronary artery calcification exhibit notable sex differences in clinical presentation, particularly concerning the role of ...

Automated ventricular and midline segmentation in cranial ultrasound with metrology.

Ultrasound imaging through sonolucent cranial implants is an emerging modality for post-neurosurgical monitoring of the adult brain, but quantitative ...

Long-Term Exposure to PM2.5 Constituents and Coronary Heart Disease Risk in China.

BACKGROUND: In China, the associations between long-term fine particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) exposure and coronary heart...

Correction to: A streamlined CMR-derived machine-learning model for estimating cardiovascular biological age: development and validation in the UK-biobank and multi-ethnic study of atherosclerosis.