Atherosclerosis

Physics-informed graph neural networks for flow field estimation in carotid arteries.

Hemodynamic quantities are valuable biomedical risk factors for cardiovascular pathology such as atherosclerosis. Non-invasive, in-vivo measurement of these quantities can only be performed using a select number of modalities that are not widely available, such as 4D flow magnetic resonance imaging (MRI). In this work, we create a surrogate model for hemodynamic flow field estimation, powered by m...

Artificial Intelligence-assisted Diagnosis of Carotid Artery Calcifications on Panoramic Radiographs: A Meta-analysis.

Carotid artery calcifications (CACs), a known risk factor for stroke, can be detected on panoramic radiographs (PRs). However, this clinically significant pathophysiological condition has long been underdiagnosed due to insufficient training and expertise among dentists. Artificial intelligence (AI) may serve as a valuable tool to aid dentists in detecting CACs on PRs. This meta-analysis was condu...

Commercial AI platforms improve reproducibility but fail to meet clinical precision thresholds for intracranial aneurysm measurement: implications for serial surveillance.

BACKGROUND: Intracranial aneurysm affect 3-7% of the global population, with rupture causing > 80% of non-traumatic subarachnoid hemorrhage and approx...

Development and validation of a computed tomography myocardial perfusion imaging radiomic model for major adverse cardiovascular events prediction: a multicenter study.

AIMS: Accurate prediction of major adverse cardiovascular events (MACE) is crucial for risk stratification in patients with suspected coronary artery ...

Development and validation of interpretable machine learning models for predicting long-term functional outcomes in elderly patients with aneurysmal subarachnoid hemorrhage.

BACKGROUND: Accurate prognostication in elderly patients with aneurysmal subarachnoid hemorrhage (aSAH) remains challenging due to high morbidity and ...

Synergistic DBNDD1-GDF15 Signaling Activates the NF-κB Pathway to Promote Colorectal Cancer Progression.

UNLABELLED: Colorectal cancer is a highly lethal gastrointestinal tract malignancy whose pathogenesis and molecular drivers are not fully understood. ...

Multi-omics profiling of chronic immune-mediated skin diseases: SKINERGY protocol and strategic evaluation.

BACKGROUND: The Dutch flagship project Next Generation ImmunoDermatology (NGID) aims to profile five chronic immune-mediated inflammatory skin disease...

Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: A cross-sectional SHAP-based analysis of NHANES 2009-2023.

Depression (DEP) is a common yet underdiagnosed comorbidity in adults with type 2 diabetes mellitus (T2DM), worsening glycemic control and increasing ...

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 su...

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-vas...

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...