Atherosclerosis

Physics constrained graph neural network for real time prediction of intracranial aneurysm hemodynamics.

Intracranial aneurysms (IAs) are life-threatening vascular conditions requiring accurate risk assessment to guide treatment. Hemodynamic biomarkers such as wall shear stress and oscillatory shear index are promising predictors of rupture risk but remain underused clinically due to the high computational cost of traditional CFD methods. We propose a physics-constrained graph neural network (GNN) fr...

Intravitreal faricimab in patients with refractory diabetic macular edema: 6-month fluid analysis using artificial intelligence.

PURPOSE: Diabetic macular edema (DME) is a leading cause of vision loss in patients with diabetes. In developed countries, intravitreal (IVT) anti-vascular endothelial growth factor (VEGF) injections are the standard-of-care first-line treatment for DME. However, despite the efficacy of anti-VEGF and associated improvements in prognosis, some patients show only a partial response and continue to r...

Association between the remnant cholesterol and the risk of new-onset chronic diseases: evidence from CHARLS.

Assessment of cognitive load through photoplethysmography and bioimpedance responses during mental arithmetic tasks.

Accurate assessment of cognitive load is vital in cognitive research and human-machine interaction. This study investigates a multimodal approach for ...

Development and interpretation of a dual-energy CT-based deep learning radiomics model for predicting new cerebral ischemic lesions after carotid artery stenting: a multicenter study.

OBJECTIVES: Early recognition of individuals at elevated risk for new ipsilateral ischemic lesions (NIILs) after carotid artery stenting (CAS) is vita...

Comparison of Image Quality Reconstructed Using Iterative Reconstruction and Deep Learning Algorithms Under Varying Dose Reductions in Dual-Energy Carotid CT Angiography.

Carotid CT angiography (CTA) is valuable for diagnosing carotid artery disease but involves radiation and contrast agent risks. Deep Learning Image Re...

Single-cell Transcriptomic Profiling Reveals Diagnostic of T Cell-platelet Aggregates in Peripheral Blood for Coronary Vulnerable Plaques.

Acute coronary syndrome, driven by vulnerable plaque (VP) instability, is a major cause of cardiovascular mortality. Current diagnostic methods for VP...

Leveraging in-silico deep learning and computational analyses to predict the pathogenicity of ROBO4 variants of uncertain significance in aortic aneurysm and dissection patients.

Variants of uncertain significance (VUS) in genes implicated in thoracic aortic aneurysm (TAA) present clinical challenges due to ambiguous pathogenic...

Clinical-radiological machine learning model for non-invasive diagnosis and stratification of peripheral artery disease: a multicenter study.

BACKGROUND AND OBJECTIVE: Peripheral artery disease (PAD) is an atherosclerotic disorder prevalent in the elderly that leads to peripheral function de...

A hybrid swin transformer-BiLSTM framework and ensemble learning for multimodal brain stroke detection and risk prediction.

Stroke is one of the leading causes of mortality and long-term disability worldwide, primarily resulting from the sudden disruption of cerebral blood ...

Multi-omics Analysis Reveals the Prognostic and Therapeutic Value of TGF-β Signaling-related Genes in Idiopathic Pulmonary Fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease with a survival rate comparable to or worse than that of many cancers. Prop...

[Efficacy prediction of acupuncture and moxibustion combined with conventional treatment for PCOS-IR based on real-world data: machine learning and interpretability analysis].

OBJECTIVE: To construct an efficacy prediction model for polycystic ovary syndrome with insulin resistance (PCOS-IR) treated with acupuncture and moxi...

Identification of a potential relationship between pigmented villonodular synovitis and atherosclerosis using comprehensive bioinformatics analyses.

BACKGROUND: This study investigates the pathogenesis of Pigmented Villonodular Synovitis (PVNS) using bioinformatics approaches shared with atheroscle...

Cardiovascular measures from abdominal MRI provide insights into abdominal vessel genetic architecture.

BACKGROUND: Cardiovascular disease remains a major source of morbidity and mortality, and population imaging studies have yielded insights into diseas...

Advancements in psoriasis classification using custom transfer learning algorithms.

Psoriasis is a skin disorder which mainly occurs as a rash, scaly areas and an itchy skin. The symptoms usually occur on the chest, elbows, and the sc...

Artificial Intelligence-derived Measurements of Myosteatosis from Coronary Artery Calcium CT Scans to Predict COPD: The Multi-Ethnic Study of Atherosclerosis.

Purpose To evaluate the predictive value of myosteatosis as an opportunistic finding in coronary artery calcium (CAC) CT scans for clinically diagnose...

Targeted blood proteome profiling using NULISAseq identifies a high-performance biomarker panel for Aβ pathology quantification and staging.

INTRODUCTION: While current blood-based biomarkers for Alzheimer's disease (AD) are effective for determining amyloid beta (Aβ) pathology positivity/n...

Integrative Transcriptomic and Bioinformatics Approaches Combined With Transformer Models Identify Key Gene Networks in Atherosclerosis.

This study aimed to prioritize candidate transcriptomic mediators associated with human atherosclerosis progression by integrating transformer-based d...

Deep learning for high-resolution magnetic resonance vessel wall imaging: image reconstruction, stenosis diagnosis and plaque calculation.

OBJECTIVES: This study developed an automated AI-based method for accurate image reconstruction, stenosis detection and plaque calculation in high-res...

Prediction of mortality, bleeding, and ischaemic events in patients with cancer and acute coronary syndrome: a model development and validation study.

BACKGROUND: Accurate assessment of mortality, bleeding, and atherothrombotic risk in patients with cancer and acute coronary syndrome could inform nov...