Metabolic Syndrome

Machine Learning Classification of Prevalent Chronic Disease Using Multidimensional Social, Behavioral, and Psychological Determinants: A Cross-Sectional Analysis of the 2024 National Health Interview Survey.

BACKGROUND: Chronic diseases account for approximately 90% of the $4.5 trillion annual healthcare expenditure in the United States. While traditional clinical risk factors have been extensively studied, the predictive utility of multidimensional social determinants of health (SDOH), including psychosocial factors such as loneliness, psychological distress, and social support, remains inadequately ...

Deep Learning-based Automated Segmentation of Ultra-Widefield Retinal Vasculature for Cardiometabolic Disease Association Analysis.

Retinal vessel analysis in ultra-widefield (UWF) images provides a unique opportunity for large-scale assessment of systemic microvascular health. However, accurate segmentation in true-color UWF images remains challenging due to the large field of view, complex background, and reduced vessel contrast. To address these challenges, we develop ECS-Net, a dedicated deep learning (DL) framework for re...

Beyond the guidelines: Vascular function as the central determinant and therapeutic target in hypertension.

Hypertension has traditionally been defined and managed according to brachial blood pressure levels. Although this pressure-centric strategy has signi...

The FERM guild: a differentially correlated microbial module drives hypertension via metabolic flux perturbations.

UNLABELLED: Hypertension is a major risk factor for cardiovascular diseases, with changes in gut microbiota composition and function being closely ass...

Plasma proteomics linking primary and secondary diseases: Insights into molecular mediation from UK Biobank data.

BACKGROUND: Diabetes, hypertension, and dyslipidemia are major risk factors for cardiovascular, neurological, renal, and pulmonary diseases, yet clini...

Machine Learning Approaches to Identify Influential Factors of the Comorbid Psychiatric Symptoms and Hypertension Among Rural Adults in Bangladesh: A Cross-Sectional Study.

BACKGROUND AND AIM: The burden of both psychiatric symptoms (anxiety and/or depression) and hypertension poses significant public health challenges in...

Clinical and Echocardiographic Factors Associated With AI-Estimated Atrial Fibrillation Likelihood During Sinus Rhythm in Patients With Documented Paroxysmal Atrial Fibrillation.

BACKGROUND: Artificial intelligence-enabled electrocardiography (AI-ECG) has emerged as a promising tool for identifying patients with atrial fibrilla...

Prediction of coronary atherosclerosis progression in type 2 diabetes mellitus based on AI-derived CCTA parameters and clinical factors: a follow-up study.

OBJECTIVE: To develop a predictive model for coronary atherosclerosis progression in patients with type 2 diabetes mellitus (T2DM) based on Artificial...

[Artificial intelligence in hypertension: where do we stand?].

Artificial intelligence (AI) is entering the study of hypertension, serving both primarily clinical purposes - to assist practicing physicians - and r...

Identifying the Most Important Influencing Factors Based on Demographic Information, Nutrition, Physical Activity, Leisure Time, and Underlying Diseases in the Severity of Disease in COVID-19 Patients Using Data Mining Techniques.

BACKGROUND AND AIMS: The COVID-19 pandemic has affected millions of individuals worldwide and resulted in substantial mortality. Data mining and machi...

Cardiovascular risks of plastic-associated chemicals: Integrating mixture modeling and SHAP-explained machine learning to unravel linear and non-linear associations.

INTRODUCTION: Plastic-associated chemicals (PACs) are widely detected environmental contaminants, yet their cardiovascular relevance in the context of...

Integrating Multimodal Data and Genomics for a Comprehensive Assessment of Cardiovascular Aging and Its Impact.

BACKGROUND: Age-related structural and functional remodeling of the heart and vessels increases cardiovascular disease (CVD) risk, yet comprehensive a...

Predicting medication non-adherence using machine learning: Incorporating Complementary and Alternative Medicine (CAM) beliefs in Malaysian chronic disease patients.

Medication non-adherence among chronic disease patients remains a major contributor to poor health outcomes and medication wastage, particularly in mu...

AI-derived oocyte morphology and follicular fluid biomarkers in donors.

Oocyte quality is a key determinant of reproductive success, yet its assessment in assisted reproduction largely relies on subjective morphological cr...

Intracranial pressure physiology, monitoring and individualized management in the acute brain injured patient.

Acute brain injury (ABI), including traumatic brain injury, ischemic and hemorrhagic stroke, is associated with high morbidity and mortality, which is...

Heterogeneity in the association between antihypertensive medications and Alzheimer's disease and related dementias risk: A multidimensional machine learning analysis to inform drug repurposing.

BackgroundAlzheimer's disease and related dementias (ADRD) place an immense burden on patients, families, and health systems in the United States. Hyp...

Data-driven endocrine-metabolic phenotypes in young women with polycystic ovary syndrome and associations with cardiometabolic risk markers.

Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder associated with reproductive dysfunction and increased cardiometabolic risk. Co...

Long-Term Particulate Matter Exposure and Coronary Inflammation: A Large-Scale Cohort Study Assessed by Pericoronary Fat Attenuation Index.

Particulate matter (PM) is known to accelerate atherosclerosis through systemic inflammation, yet its specific impact on local coronary inflammation r...

Association Between Inflammatory Biomarkers And Carotid Ultrasound Parameters In The Northern Manhattan Stroke Study.

Inflammation contributes to atherosclerosis and vascular remodeling, but the immune pathways associated with distinct carotid ultrasound phenotypes, i...

Phenotypic Clustering of Idiopathic Pulmonary Arterial Hypertension: Insights Into Pulmonary Vascular and Cardiometabolic Co-Morbidity Trajectories.

Idiopathic pulmonary arterial hypertension (IPAH) exhibits significant clinical heterogeneity, necessitating a precision medicine approach. This study...