Atherosclerosis

Synthetic data generation from a stenosed carotid arteries using sensitivity analysis: an application to AI models.

In artificial intelligence (AI), data dramatically impacts AI models performance, accuracy, and reliability. High-quality data enables models to make better predictions and produce more reliable outcomes. Poor data quality or lack of data can lead to flawed results and cause poor performance and predictions. Sensitivity analysis could play a vital role to generate synthetic dataset from any valida...

Integrated Transcriptomic Analysis and Machine Learning Identify THY1 as a Key Regulator of Cancer-Associated Fibroblast Infiltration, Promoting Malignant Progression and Immune Escape in Gastric Cancer.

BACKGROUND: Heterogeneity in cancer-associated fibroblast (CAF) infiltration within the tumor microenvironment is closely associated with gastric cancer progression and immune evasion; however, precise CAF-related diagnostic markers and actionable therapeutic targets remain scarce. METHODS: Weighted gene coexpression network analysis (WGCNA) was employed to screen CAF-related coexpression modules....

Exploring and validating hub genes associated with atopic dermatitis through weighted gene co-expression network analysis and machine learning.

This study aimed to identify novel biomarkers of atopic dermatitis (AD) and investigate their pathogenic mechanisms. We analyzed 7 AD-related datasets...

Computed Tomographic Angiography-Based Radiomics Predicted Stroke Recurrence in Patients With Symptomatic Intracranial Atherosclerotic Stenosis.

BACKGROUND: The aim of the current study was to investigate the predictive values of computed tomographic angiography-derived radiomics features (RFs)...

Opportunistic Screening of Carotid Atherosclerosis and Cardiovascular Mortality Risk Using Chest Radiographs: A Comparative Study of Foundation Models.

BACKGROUND: Cardiovascular disease (CVD) remains a leading cause of death, but population-level screening for atherosclerosis often depends on special...

Abdominal vascular calcification at CT: opportunistic quantification and imaging-based risk stratification.

Abdominal vascular calcification is increasingly recognized as a clinically relevant marker of systemic atherosclerotic burden and regional vascular d...

Integrative transcriptomic and experimental analyses prioritize TPT1 as a PANoptosis-associated candidate molecular marker in sarcopenia.

BACKGROUND: Sarcopenia lacks sensitive molecular markers for early detection, and its relationship with integrated inflammatory cell-death programs re...

Integrating machine learning and multi-omics analysis to identify and validate key genes associated with periodontitis.

AIMS: Early detection and intervention are crucial for effective management of periodontitis. Our study aims to identify diagnostic biomarkers for per...

From In Silico De Novo Generation to In Vitro Functional Validation: Discovery of Multifunctional Antithrombotic Peptides from Food-Derived Proteins via a Hybrid LSTM-GCN and Molecular Simulation Pipeline.

Cardiovascular thromboses bring heavy global health burdens, while traditional screening of food-derived antithrombotic peptides is inefficient. This ...

Multicenter External Validation of an AI-Based Funduscopic Carotid Atherosclerosis Score and Assessment of Its Association With Coronary Artery Calcification: External Validation Study.

BACKGROUND: Screening for atherosclerosis is essential for early intervention, but conventional screening methods are often invasive and resource-inte...

MACHINE LEARNING VERSUS PENALISED LOGISTIC REGRESSION FOR PREDICTING IN-HOSPITAL MORTALITY IN RUPTURED ABDOMINAL AORTIC ANEURYSM: A COMPARISON USING A UNIFORM VALIDATION FRAMEWORK.

BACKGROUND: Ruptured abdominal aortic aneurysm (rAAA) remains associated with substantial in-hospital mortality. Although machine-learning methods can...

Digital Oral Health beyond Professional Dental Care Settings: A Scoping Review of Technologies and Applications from Prevention to Early Detection.

BACKGROUND: Oral non-communicable diseases impose a substantial and unequally distributed global burden. Digital technologies have the potential to su...

Macrophage Lipid Homeostasis Drives IVDD via a Senescence-Dependent Impairment of Efferocytosis.

Intervertebral disc degeneration (IVDD) is a major contributor to low back pain, but the immune-metabolic events that sustain disc inflammation remain...

CASP1 as a key autophagy-related gene in atherosclerosis: Identification by bioinformatics analysis and experimental validation.

OBJECTIVE: This study identified potential autophagy-related genes (ARGs) in atherosclerosis using bioinformatics strategies, aiming to explore novel ...

Artificial intelligence-enhanced management system for secondary prevention of coronary heart disease: a randomized clinical trial.

BACKGROUND: Secondary prevention of coronary heart disease (CHD) remains suboptimal due to fragmented care and therapeutic inertia. While digital heal...

VCAM-1 Serves as a Biomarker for Discriminating Eosinophilic CRSwNP and Regulates IL-13-Induced Vascular Remodeling.

BackgroundChronic rhinosinusitis with nasal polyps (CRSwNP) is a highly heterogeneous inflammatory disease with distinct inflammatory endotypes. This ...

Short-interval coronary plaque remodeling assessed by serial AI-quantified coronary CTA during intensive plaque-directed therapy.

Linking Metabolic Subgroups and Adverse Pregnancy Outcomes in GDM: A Complementary Analytic Approach of Logistic Regressions and Machine Learning.

AIMS: Associations between metabolic heterogeneity in women with gestational diabetes mellitus (GDM) and adverse pregnancy outcomes have often been ex...

Microfluidic Chip Platforms for Red Blood Cell Storage Lesion Quality Control and Precision Transfusion.

Red blood cell (RBC) transfusion is a core clinical intervention. However, hypothermic storage induces progressive biochemical, structural, and functi...

Comparative analysis of machine learning techniques for cardiovascular disease prediction.

BACKGROUND AND OBJECTIVES: Early and accurate prediction of cardiovascular disease (CVD) is fundamental for reducing morbidity and mortality. Machine ...