Atherosclerosis

A hybrid pipeline for carotid artery segmentation using YOLOv11n and contour models.

Carotid artery segmentation is critical for determining the degree of vascular disease, and for recommending treatment options. Early detection of carotid atherosclerosis is critical for preventing stroke. Stroke-related brain damage can cause deficits in speech or vision, and large strokes can be fatal. However, automatic segmentation of the carotid artery lumen remains difficult due to the low q...

An interpretable machine learning model for early risk stratification of medium-to-giant coronary artery aneurysm in Kawasaki disease: development and external validation.

BACKGROUND: Medium-to-giant coronary artery aneurysm (MGCAA) represents the most severe complication of Kawasaki disease (KD) and remains difficult to identify early. Existing risk scores are not tailored for MGCAA and lack external validation. Interpretable machine learning (ML) approaches may improve early risk stratification. METHODS: We retrospectively analyzed 443 patients from Fuzhou (develo...

Machine learning derived ORC6 as a hub biomarker for predicting tumor microenvironment, prognoses, and therapeutic responses in lung adenocarcinoma.

The origin recognition complex (ORC) is a DNA-binding complex composed of six subunits involved in DNA replication in cancer cells. The prognostic and...

Molecular mechanisms of exercise-induced improvements in Alzheimer's disease: a focus on lipid homeostasis.

Alzheimer's disease (AD) is the most prevalent type of dementia, and its pathophysiological mechanisms involve multiple factors, including genomic fac...

Mapping the subgingival HerBiome and HisBiome over the human healthspan.

BACKGROUND: Understanding the intricate relationship between sex, age, and the oral microbiome is crucial for deciphering the onset and progression of...

Artificial Intelligence Applications in COVID-19-Associated Coagulopathy: Lessons Learned.

Coronavirus disease 2019 (COVID-19)-associated coagulopathy (CAC) is a thromboinflammatory syndrome marked by endothelial injury, micro- and macrovasc...

SR-FTIR spectroscopy combined with machine learning reveals the alterations of biochemical composition in tendinopathy.

Tendinopathy is a musculoskeletal disorder characterized by pathological extracellular matrix remodeling, yet the associated biochemical alterations r...

Integrated bioinformatics and machine learning, research on specific biomarkers for large-artery atherosclerosis stroke.

Large-artery atherosclerosis stroke (LAA) is the main subtype of ischemic stroke. Currently, the diagnosis of LAA is confirmed through magnetic resona...

Palmatine ameliorates MASLD in type 2 diabetes by modulating hepatic apoptosis and inflammation.

Type 2 diabetes mellitus (T2DM) is a major risk factor for metabolic dysfunction-associated steatotic liver disease (MASLD), and their convergence pre...

Endothelial cell senescence shapes T cell activity in late-stage of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a leading cause of death with few effective therapies. While clinical staging distinguishes mild to ve...

CorvisST biomechanical indices in the diagnosis of corneal stromal and endothelial disorders: an artificial intelligence-based comparative study.

AIMS: To analyse the value of the CorvisST indices in diagnosing corneal stromal and endothelial disorders (CSEDs). METHODS: This institutional retros...

Artificial intelligence models for osteoporosis risk prediction in postmenopausal women with CKD: A cross-sectional analysis of NHANES 2005 to 2018.

Artificial intelligence (AI) can transform osteoporosis (OP) screening, but its application in high-risk, complex populations like postmenopausal wome...

Cross-sectional evaluation of cardiovascular biological age using point-of-care ultrasound.

AIMS: Biological age is increasingly recognized as a superior predictor of morbidity, mortality, compared with chronological age. Artificial intellige...

Cuproptosis of endothelial cells in a hypoxic environment: from molecular classification to PMAIP1-targeted intervention.

Inflammatory protein profiling in immune cells identifies molecular signatures for enhanced diagnostic precision in psoriatic arthritis.

Psoriatic arthritis (PsA) lacks reliable biomarkers to support early diagnosis and disease stratification. This study aimed to identify protein signat...

Percutaneous coronary intervention in high bleeding risk patients: a review of contemporary management strategies.

INTRODUCTION: High bleeding risk (HBR) affects over one-third of patients undergoing percutaneous coronary intervention (PCI) and is associated with e...

Machine Learning-Based Risk Prediction for Coronary Heart Disease Complicated by Hyperhomocysteinemia: Retrospective Study.

BACKGROUND: Hyperhomocysteinemia (HHcy) is recognized as an independent risk factor for coronary heart disease (CHD), yet accurately predicting CHD ri...

SEQUAL: Self-refining and effective querying active learning with pseudo label divergence score for carotid intima-media segmentation in ultrasound.

Deep learning has achieved remarkable performance in carotid intima-media (CIM) segmentation from ultrasound images, but its clinical applicability re...

Identification of hub targets involved in carotid atherosclerosis through bioinformatics and machine learning approaches.

Elucidating the mechanism of plasticizers associated with atherosclerosis through network toxicology, bulk RNA sequencing, and single-cell RNA sequencing analysis.

PURPOSE: This study aims to screen and identify potential atherosclerosis (AS) biomarkers associated with common plasticizer exposure, providing a bas...