Atherosclerosis

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 macrovascular thrombosis, and, in a minority, late consumptive bleeding. D-dimer elevation was found to be one of the most consistent laboratory abnormalities and an established marker of severity. In this review, we explore how artificial intelligence method...

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 presents a significant therapeutic challenge. Palmatine, an isoquinoline alkaloid with lipid-regulating and anti-inflammatory properties, is a promising candidate; however, its multi-target mechanisms remain undefined. To address this, we employed a seq...

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...

Development and Validation of a Machine Learning Model for Incident Heart Failure Prediction in Chronic Kidney Disease: A Multicenter Cohort Study.

BACKGROUND: Chronic kidney disease (CKD) and heart failure (HF) share pathophysiological mechanisms, rendering HF one of the most burdensome cardiovas...

Developing a practical machine learning model to predict post implantation syndrome after endovascular aneurysm repair.

BACKGROUND: Post-implantation syndrome (PIS) is recognized as a systemic inflammatory response following endovascular aneurysm repair (EVAR), characte...

Towards real-time sleep stage classification: A deep learning approach leveraging PPG and ECG.

OBJECTIVE: This work aims to enable adaptive Consumer Sleep Technologies (CSTs) for sleep intervention by developing a deep learning model for sleep s...

An open B-mode ultrasound database for deep learning-based atherosclerotic plaque segmentation.

Cardiovascular events, predominantly ischemic, account for approximately 32% of global mortality and are expected to increase approximately 30% by 203...

Explainable artificial intelligence for early Alzheimer's diagnosis using enhanced grey relational features and multimodal data.

Alzheimer's disease, a progressive neurodegenerative disorder, presents a growing global health challenge due to its increasing prevalence and lack of...

Artificial Intelligence-Driven Electrocardiogram Screening for Asymptomatic Left Ventricular Systolic Dysfunction in the General Population.

BACKGROUND: Asymptomatic left ventricular systolic dysfunction (LVSD) is a well-established precursor of overt heart failure (HF), yet it often remain...

Single-cell sequencing combined with transcriptome sequencing to reveal the molecular mechanisms related to integrated stress responses in atherosclerosis.