Atherosclerosis

Integrating single-cell analysis and machine learning to identify COPD hub genes and explore the intervention mechanism of effective component compatibility of Bufei Yishen formula III.

ETHNOPHARMACOLOGICAL RELEVANCE: Chronic obstructive pulmonary disease (COPD) is a prevalent condition that poses a major threat to public health. Endothelial cells play a critical role in COPD pathogenesis. Recent evidence suggests that the effective-component combination of Bufei Yishen formula III (ECC-BYF III) significantly improves clinical symptoms and quality of life in COPD patients.

Artery fragment guided approach for enhancing cerebral aneurysm detection in TOF-MRA imaging.

BACKGROUND: Cerebral aneurysms are a type of cerebrovascular disease that poses a severe threat to life and health. Early screening using Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) can effectively reduce the risk of rupture. Despite the importance of early detection, manual image screening remains a laborious and inefficient process. The current thrust of research in computer-aided de...

A plaque recognition algorithm for coronary OCT images by Dense Atrous Convolution and attention mechanism.

Currently, plaque segmentation in Optical Coherence Tomography (OCT) images of coronary arteries is primarily carried out manually by physicians, and ...

Identification of macrophage-associated diagnostic biomarkers and molecular subtypes in gestational diabetes mellitus based on machine learning.

Gestational diabetes mellitus (GDM) is a common metabolic disorder during pregnancy, involving multiple immune and inflammatory factors. Macrophages p...

Inconsistency of AI in intracranial aneurysm detection with varying dose and image reconstruction.

Scanner-related changes in data quality are common in medical imaging, yet monitoring their impact on diagnostic AI performance remains challenging. I...

Research on ischemic stroke risk assessment based on CTA radiomics and machine learning.

BACKGROUND: The study explores the value of a model constructed by integrating CTA-based carotid plaque radiomic features, clinical risk factors, and ...

Shotgun Metagenomics Identifies in a Cross-Sectional Setting Improved Plaque Microbiome Biomarkers for Peri-Implant Diseases.

AIM: This observational study aimed to verify and improve the predictive value of plaque microbiome of patients with dental implant for peri-implant d...

Identification of key proteins and pathways in myocardial infarction using machine learning approaches.

Acute myocardial infarction (AMI) is a leading cause of global morbidity and mortality, requiring deeper insights into its molecular mechanisms for im...

A hybrid GAN-based deep learning framework for thermogram-based breast cancer detection.

Breast cancer remains one of the most prevalent and life-threatening diseases among women worldwide, necessitating early and accurate detection method...

Automated periodontal assessment in orthodontic patients: a dual CNN framework.

OBJECTIVE: The aim of this study was to develop convolutional neural network (CNN)-based systems to diagnose calculus, plaque, gingival hyperplasia an...

Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis.

Diabetes Mellitus is a chronic metabolic disorder affecting a substantial global population leading to complications such as retinopathy, nephropathy,...

A novel outreach approach for identification of familial hypercholesterolemia: Interview-based formative evaluation to improve healthcare access and quality.

BACKGROUND: Familial hypercholesterolemia (FH) is a genetic condition which elevates cholesterol levels and increases risk of premature cardiac events...

The Application of Machine Learning in Warfarin Dose Precision for Diabetic Patients Treated with Statins: A Comparative Study.

PURPOSE: To evaluate the impact of statin therapy on warfarin dose requirements in diabetic patients and to assess the performance of various machine ...

Single-tooth resolved, whole-mouth prediction of early childhood caries via spatiotemporal variations of plaque microbiota.

Early childhood caries (ECC) exhibits tooth specificity, highlighting the need for single-tooth-level prevention. We profiled 2,504 dental plaque micr...

Evaluating the impact of metabolic indicators and scores on cardiovascular events using machine learning.

Cardiovascular diseases such as coronary artery disease, myocardial infarction, and heart failure impact millions of people annually globally and are ...

Machine Learning-Based Rupture Risk Prediction for Intracranial Aneurysms: A Systematic Review and Meta-Analysis.

BACKGROUND AND OBJECTIVES: Aneurysm risk prediction remains an imprecise science that places patients at risk for either over or undertreatment. Machi...

Unraveling the TEC-associated landscape in hepatocellular carcinoma: a comprehensive study based on multi-omics analyses.

The tumor microenvironment (TME) plays a pivotal role in tumor progression, immune evasion, and therapeutic responses. Among its key components, endot...

Biomarkers for human donor lung assessment during ex vivo lung perfusion.

Lung transplantation remains the only curative treatment option for patients with end-stage lung disease, yet limited donor lung availability and util...

Enhancing precision in aneurysm volume measurement: A comparative study of techniques including an artificial intelligence-based method for endovascular coiling.

BACKGROUND: Durable occlusion after endovascular coiling can be compromised by recanalization, underscoring the need for accurate cerebral aneurysm as...

Effect of low-dose colchicine on pericoronary inflammation and coronary plaque composition in chronic coronary disease: a subanalysis of the LoDoCo2 trial.

BACKGROUND: Low-dose colchicine (0.5 mg once daily) reduces the risk of major cardiovascular events in coronary disease, but its mechanism of action i...