Latest AI and machine learning research in atherosclerosis for healthcare professionals.
BACKGROUND: Coronary Computed Tomography Angiography (CCTA) is an established tool for assessing coronary artery disease. CCTA determined total coronary artery plaque volume predicts cardiovascular events, but manual quantification is impractical for routine use. Deep learning-based methods offer a promising solution for automated plaque volume assessment. METHODS: We developed and validated a nov...
BACKGROUND: Circadian syndrome (CircS) augments the conventional metabolic syndrome construct by adding disturbed sleep and depressive features. Whether composite metabolic indices that combine insulin-resistance, atherogenic-lipid, and inflammatory signals can forecast CircS prior to its onset has not been systematically investigated. The present work evaluated eight such composite markers in a p...
BACKGROUND: Based on machine learning prediction models, we explored the anemia treatment attainment of patients on maintenance hemodialysis (MHD) and...
Cellular senescence is increasingly recognized as a fundamental driver of cardiovascular ageing; however, its molecular heterogeneity, cell-type speci...
PURPOSE: To develop and validate machine learning (ML) models for predicting early postoperative corneal edema (CE) after phacoemulsification in patie...
OBJECTIVES: To evaluate the reproducibility of plaque quantification from serial cardiac computed tomography (CCTA) scans by a systematic side-by-side...
PURPOSE: Several semiquantitative coronary computed tomography angiography (CCTA) scores including different parameters describing stenosis degree, pl...
BACKGROUND AND AIMS: Atherosclerosis results from cellular and extracellular changes in the arterial wall, preceded by molecular shifts that initiate ...
Sepsis remains a formidable challenge in critical care, and is characterized by profound circulatory and cellular abnormalities driven by both systemi...
Peripheral artery disease (PAD) is a common manifestation of atherosclerotic cardiovascular disease (ASCVD) that is underdiagnosed in clinical practic...
BACKGROUND: Diabetic retinopathy (DR) is a leading cause of vision loss, yet conventional retinal screening remains costly and resource-intensive. Thi...
BACKGROUND: Lean metabolic dysfunction-associated fatty liver disease (MAFLD) is increasingly recognized but often goes unnoticed during health checku...
BACKGROUND: The rising incidence of youth-onset type 2 diabetes mellitus (T2DM), along with the risk of early cardiovascular complications, is concern...
Thoracic aortic aneurysms arise from a combination of biological and mechanical factors. Current clinical guidelines use size and rate of expansion to...
Glioblastoma (GBM), the most aggressive primary brain tumor, develops within a tumor microenvironment (TME) dominated by tumor-associated macrophages ...
BACKGROUND: While the single-point insulin sensitivity estimator (SPISE) shows promise as an insulin resistance biomarker, its association with cardio...
Coronary artery disease assessment has long focused on stenosis severity, yet luminal narrowing alone fails to capture ischemic burden, plaque vulnera...
BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) and Heart Failure with preserved Ejection Fraction (HFpEF) frequently coexist, leading to inc...
OBJECTIVES: This systematic review and meta-analysis aimed to evaluate the strength of the associations between digital technologies and reference met...
Hepatic fibrosis is a pivotal stage in which chronic liver disease progresses from reversible injury to decompensation. Liver sinusoidal endothelial c...