Atherosclerosis

Decoding the Genetic Architecture of Acute Coronary Syndrome: A Review on Integrated Medical Modeling.

UNLABELLED: Genetic mutations contribute significantly to the complexity of understanding Acute Coronary Syndrome (ACS). Artificial Intelligence (AI) models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN), have been integrated as an advanced approach to uncover hidden mutation clues for early detection and prevention of life-thr...

Targeting the Myocardial Microenvironment: Novel Antiviral Strategies and Therapeutic Perspectives for Coxsackievirus B-Induced Myocarditis.

Coxsackievirus B3 is a primary cause of viral myocarditis, with ≈20% of cases progressing to dilated cardiomyopathy. Despite its clinical significance, therapeutic strategies remain limited. The pathogenesis of coxsackievirus B3-induced myocarditis is complex, centered on the virus's ability to hijack the myocardial microenvironment, which is composed of various cell types and their interactions, ...

Super learner model for predicting carotid plaque regression in type 2 diabetes on PCSK9 inhibitors.

OBJECTIVES: Evidence regarding the effects of proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors on carotid plaque regression in patient...

EMBC Special Issue: Non-invasive BP Estimation via Carotid-Brachial-Radial Coupling: A Physics-Informed Asymmetric Cycle Network Approach.

Photoplethysmogram (PPG) based cuffless blood pressure (BP) monitoring holds significant potential to revolutionize hypertension management. However, ...

Trusting Generative AI for Health Advice: Preregistered Survey Experiment.

BACKGROUND: Generative artificial intelligence (AI) systems are increasingly used for health information seeking, yet it remains unclear how the publi...

Burden trajectories of stroke attributable to lipid-glucose dysfunction and biomarker validation: evidence from the global burden of disease (GBD) 2023 and the China health and retirement longitudinal study (CHARLS).

BACKGROUND: Metabolic dysfunction is an important contributor to stroke burden and may also help identify individuals at higher future risk of stroke....

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study.

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage increases risk of vascular events...

Integrating epidemiological and transcriptomic data reveals novel lipid metabolic drivers of obstructive sleep apnea.

BACKGROUND: Obstructive sleep apnea (OSA) is characterized by recurrent upper airway obstruction during sleep and is frequently accompanied by dyslipi...

Identifying Patients at Elevated Risk of Stroke After.

BACKGROUND: Transcarotid artery revascularization (TCAR) has assumed a significant role in the surgical treatment of extracranial carotid occlusive di...

A machine learning-based framework for predicting hypertension using serum hematological factors.

Hypertension (HTN) is a leading global cause of cardiovascular disease (CVD) and all-cause mortality, underscoring the need for early detection and in...

Association between visceral adiposity index and delayed union/nonunion after tibial or femoral shaft fractures: a single-center retrospective cohort study.

BACKGROUND: Delayed union and nonunion remain clinically important complications after tibial and femoral shaft fractures. Although traditional risk f...

Integrating 2.5D multi-modal CT imaging with serum triglycerides for early risk stratification in hypertriglyceridemia-induced acute pancreatitis: A multicenter study.

OBJECTIVES: To develop and externally validate a clinical-radiological framework that fuses 2.5D deep learning features from dual-phase computed tomog...

Exploratory comparative analysis of automated morphologic and perfusion features derived from one-stop computed tomography angiography and computed tomography perfusion in large unruptured intracranial aneurysms.

PURPOSE: To compare rupture-related signals captured by automatically extracted computed tomography angiography (CTA) morphologic features and thresho...

Decoding chromatin regulator-LAIR1+ M2 like macrophage patterns in atherosclerosis and clinical outcomes of Lung adenocarcinoma patients: evidence from artificial intelligence-driven multi omics and in vitro validation.

Atherosclerosis (AS) is a common complication of lung adenocarcinoma (LUAD), but its underlying mechanisms in LUAD remain unclear. This study aimed to...

Synchronous wearable ultrasound for early detection of coronary and carotid artery comorbidity.

Coronary heart disease (CHD) and carotid artery disease (CAD) often co-occur. However, conventional diagnosis typically involves separate, site-by-sit...

Retinal Microvascular Signatures as Early Predictors of Cardiovascular Risk: Integrating Pathophysiology, Molecular Insights, and Artificial Intelligence.

Cardiovascular diseases (CVDs) continue to be a significant public health burden and public health emergency in the world, underscoring the importance...

Practical pathways for evaluating artificial intelligence in intracranial aneurysm detection.

Polycystin-1 and Cardiac Remodeling: From Mechanotransduction to Clinical Consequences.

PC1 (polycystin-1), traditionally viewed through the lens of renal pathophysiology in autosomal dominant polycystic kidney disease, has emerged as a c...

The role of metabolic health in neurostructural and cognitive alterations in bipolar disorders.

BACKGROUND: Bipolar disorders (BD) rank among the most disabling conditions, affecting millions worldwide. Cognitive impairment in BD is linked with b...

Experimental validation of an AI-driven digital healthcare platform for oral health behavior and plaque assessment among vietnamese children.

BACKGROUND: Oral health among children in developing countries, including Vietnam, remains a significant public health concern. Innovative approaches ...