Atherosclerosis

Machine learning integrated clinical-proteomics data identifies a 6-protein panel signature for atherosclerotic severity and enhanced patient stratification.

Atherosclerosis, a major cause of adverse cardiovascular events and mortality rates worldwide, stems...

An Open-Source Deep Learning Framework for Automated Corneal Segmentation in Anterior Segment Optical Coherence Tomography With Cross-Device External Validation.

PURPOSE: To develop a deep learning model-Cornea nnU-Net Extractor (CUNEX)-for full-thickness cornea...

Regulatory risk loci link disrupted androgen response to the pathophysiology of polycystic ovary syndrome.

A major challenge in deciphering the complex genetic landscape of polycystic ovary syndrome (PCOS) l...

Vessel Wall Imaging at 7T: State of the Art.

Intracranial vessel wall imaging (VWI) has emerged as a critical tool in neurovascular diagnostics, ...

Targeting cholesterol metabolism: a core regulator of tumor-associated macrophage plasticity and immunotherapy response.

Tumor-associated macrophages (TAMs) are one of the main immunosuppressive components in the tumor mi...

Ischaemia in tuberculous meningitis: update on pathophysiology, clinical predictors and management.

PURPOSE OF REVIEW: Tuberculous meningitis (TBM) is a severe manifestation of Mycobacterium tuberculo...

AI-Derived LA Volume Index, LA/RA and LA/LV Volume Ratios From Coronary Artery Calcium Scans Predict Long-Term Atrial Fibrillation and Stroke.

BACKGROUND: The AI-CVD initiative aims to extract actionable insights from coronary artery calcium (...

Single-cell spatiotemporal dissection of the human maternal-fetal interface.

The human maternal-fetal interface is characterized by mosaic intermingling of maternal and fetal ce...

Bias, fairness, and equity in artificial intelligence systems used in dental imaging: A systematic review.

BACKGROUND: Artificial intelligence (AI) is increasingly used in dental imaging for automated interp...

Drug repurposing in Alzheimer's disease: Emerging therapeutic strategies and promising candidates.

Alzheimer's disease is a progressive neurodegenerative disorder, and the most common cause of dement...

Elucidating the role of SF3B3 in coronary atherosclerosis: integrating bioinformatics and machine learning for advanced insights.

Magnetically controlled capsule endoscopy: Innovations, standardized practice, and emerging clinical roles.

Capsule endoscopy has transformed small bowel evaluation but remains limited for gastric examination...

Carotid Imaging: Current Concepts and Advanced Imaging.

Carotid atherosclerosis is a major cause of ischemic stroke, historically managed according to lumin...

Integrative proteomics to illuminate host-parasite interactions in malaria.

Genomic studies have transformed malaria research but provide only indirect proxies for the function...

Quantitative Coronary Atherosclerotic Plaque Burden From CCTA and the Benefit From Lipid-Lowering Medication.

BACKGROUND: We hypothesized that quantification of coronary atherosclerotic plaque burden by artific...

Physics-informed graph neural networks for real-time prediction of wall shear stress in stenotic coronary arteries.

Wall shear stress (WSS) is a key hemodynamic parameter associated with atherosclerotic plaque develo...

Towards a physics informed digital twin to predict cerebral blood flow and cerebral vascular regulation.

Cerebral blood flow is essential for brain function and is governed by cerebral perfusion pressure a...

The prognostic significance of cholesterol, high-density lipoprotein and glucose (CHG) index in evaluating all-cause mortality risk in metabolic dysfunction-associated steatotic liver disease (MASLD) individuals: evidence from two cohort studies.

Screening and classification of anti-angiogenic VEGFR2 inhibitors with supervised machine learning, deep learning and molecular docking and molecular dynamics simulation.

Vascular Endothelial Growth Factor Receptor 2 (VEGFR2) is a critical therapeutic target in cancer du...

Multimorbidity and major adverse cardiovascular events in antipsychotic users: Time-to-event prediction by explainable machine learning.

Antipsychotic treatment is associated with higher risk of major adverse cardiovascular events (MACEs...

Generation of virtual abdominal aortic aneurysm shape evolution using a physics-based G&R model and its applications to aneurysm growth prediction.

The computational growth and remodeling (G&R) of aortic aneurysms has been extensively investigated ...