Latest AI and machine learning research in atherosclerosis for healthcare professionals.
Triaptosis, an emerging form of cell death, remains poorly characterized in terms of its heterogeneity within clear cell renal cell carcinoma (ccRCC). Utilizing single-cell transcriptomics, we delineate a landscape of triaptosis heterogeneity and identify monocytes and macrophages as exhibiting the highest triaptosis activity, which further increases upon terminal differentiation. These high-activ...
INTRODUCTION: The predictive value of Banff classification in protocol transplant biopsies without specific lesions is limited. Morphometry provides precise data on microstructures, surpassing semiquantitative scores but is time-consuming. This study evaluates whether automated morphometric analysis with deep learning can predict glomerular filtration rate at 3 years using machine learning. METHOD...
BACKGROUND: Chronic obstructive pulmonary disease (COPD) remains a major global health burden and is currently the third leading cause of death worldw...
BACKGROUND: Atherosclerosis (AS) is a chronic inflammatory vascular disease that can lead to severe cardiovascular events. Ferroptosis and autophagy h...
INTRODUCTION: This study aimed to identify optical coherence tomography (OCT) biomarkers at baseline and after the loading phase (LP) of antivascular ...
OBJECTIVE: To develop and validate a multimodal deep learning model that predicts treatment responses to intravitreal anti-vascular endothelial growth...
Pediatric acute kidney injury (AKI) often presents insidiously and progresses rapidly. Traditional diagnostic criteria based on serum creatinine and u...
BACKGROUND: Long-term follow-up is essential for patients with abdominal aortic aneurysms (AAAs). Our health system implemented an AAA surveillance pr...
OBJECTIVES: To evaluate whether an artificial intelligence-based denoising (AID) algorithm can effectively attenuate body mass index (BMI)-related noi...
AIM: This study aims to develop and validate machine learning models for predicting recurrence in polypoidal choroidal vasculopathy (PCV) patients usi...
BACKGROUND: Atherosclerosis (AS) is a major global health burden. Sodium nitrite, a common environmental and dietary contaminant, has been implicated ...
Neutrophil extracellular traps (NETs) are increasingly recognized as critical mediators in vascular inflammation and remodeling, yet their molecular m...
OBJECTIVE: Sensorless alignment of two-dimensional (2D) freehand ultrasound scans for three-dimensional US (3DUS) reconstruction offers significant ad...
BACKGROUND: Predicting the progression/regression of coronary plaque burden is challenging. AIMS: We aimed to develop a deep learning model to forecas...
BACKGROUND AND PURPOSE: Ischemic stroke poses a significant global health burden. Accurately identifying symptomatic carotid atherosclerotic plaques, ...
OBJECTIVES: The aim of this study was to evaluate the feasibility and reproducibility of a novel deep learning (DL)-based coronary plaque quantificati...
PURPOSE: To investigate the feasibility of using 60 kVp coronary CT angiography (CCTA) combined with deep learning-based CT reconstruction as a screen...
BACKGROUND: Herbs, like Allium sativum, Ginkgo biloba and Nerium oleander are traditional medicinal plants that have been used to treat atherosclerosi...
PURPOSE OF REVIEW: Cardiogenic shock (CS) remains associated with high mortality despite advances in revascularization, pharmacological therapies and ...
Endovascular aneurysm repair for ruptured abdominal aortic aneurysms (RAAAs) is technically demanding due to time pressure and distorted vascular anat...