Atherosclerosis

UNICORN: a deep learning model for integrating multi-stain data in histopathology.

The integration of multi-stain histopathology images through deep learning poses a significant challenge. Current approaches struggle with data heterogeneity and missing data, as concatenating multi-stain features may not effectively model stain-specific and cross-stain interactions. We introduce UNICORN (UNiversal stain Integration network for CORonary classificatioN), a two-stage, end-to-end tra...

Applying machine learning to pharmacovigilance data: A proof-of-concept study.

AIM: Machine learning (ML) applications in pharmacovigilance remain limited and underexplored. Using data from the French National pharmacovigilance database (FNPV), this proof-of-concept study aimed to assess the feasibility of using a ML algorithm-eXtreme Gradient Boosting (XGBoost)-combined with SHapley Additive exPlanations (SHAP) analysis, to classify a well-defined drug-adverse reaction pair...

Interaction Between Air Pollution and Genetic Predisposition to Blood Pressure and LDL-C on Cardiovascular Events.

AIMS: Particulate matter ≤2.5μm (PM2.5) air pollution is a leading global environmental risk factor. We investigated the impact of PM2.5 on cardiovasc...

Plasma proteomics improves thrombosis prediction in patients with cancer and identifies targetable IL-17-driven endothelial activation.

Thrombosis remains a major cause of morbidity and mortality in patients with cancer. Existing risk models fail to reliably predict venous thromboembol...

Determinants of childhood and adolescent obesity: An explainable AI approach using the ICAD database.

OBJECTIVES: To identify the biological, behavioural, and socio-demographic determinants of childhood and adolescent obesity and evaluate how their rel...

CellVision: A Deep Learning based Image Analysis Platform to Accelerate Immuno-Plaque Assay Data Processing for Dengue Vaccine Development.

Accurately detecting patterns of interest across a large number of images presents a significant challenge in data analysis for high-throughput analyt...

Fatty acid synthesis therapy-induced senescence (FASTIS) in cancer cells.

Therapy-induced senescence (TIS) in cancer cells can be triggered by radiotherapy, chemotherapy, and certain targeted therapeutics. Here, we demonstra...

Single-cell multi-omics dissection of RevitalAge Markers uncovers age-dependent immunotherapy resistance and druggable targets in melanoma.

Aging-related molecular reprogramming profoundly influences melanoma progression and therapeutic sensitivity, yet underlying mechanisms remain poorly ...

Interpretable Machine Learning in Heavy Metal-Associated Cardiovascular and Metabolic Disease: A Review of Current Methodologies, Toxicological Insights, and Clinical Implications.

Heavy metals, including lead (Pb), cadmium (Cd), arsenic (As), and mercury (Hg), are pervasive environmental toxicants increasingly recognized as nont...

Machine learning versus deep learning for screening ischemic stroke among asymptomatic population.

Ischemic stroke puts great health burden in public. However, the diagnosis is based on head CT or MRI scanning. We aim to develop classifier models to...

Explainable artificial intelligence models in predicting major cardiovascular events: insights from the PolyIran and PolyPars prospective studies.

Cardiovascular diseases are among the leading causes of global mortality and morbidity, underscoring the need for accurate and explainable predictive ...

Chronic Total Occlusion Recanalization in a 14-Year-Old Girl With Pseudoxanthoma Elasticum: IVUS-Guided Stentless Strategy.

BACKGROUND: Pseudoxanthoma elasticum (PXE) is a hereditary disorder causing progressive arterial mineralization that may cause premature coronary dise...

Deep learning models for the detection of dental-findings and tooth-types using video data.

BACKGROUND: Oral diseases have an estimated incidence of 35.5% worldwide, yet access to dental care is often hindered by a shortage of dental professi...

Validation of Artificial Intelligence in Detecting Acute Cervical Spine Fractures on CT.

BACKGROUND: Cervical spine fractures require prompt and accurate diagnosis to minimize risk of long-term neurological impairment. Artificial intellige...

Radiomic Carotid Plaque Features Integrated into Machine Learning Models for Cardiovascular Risk Prediction.

OBJECTIVE: Carotid plaque detected by ultrasound is associated with major adverse cardiovascular events (MACE) and can be characterized using manual o...

Time-to-event ensemble machine learning approach for predicting long-term survival of abdominal aortic aneurysm patients undergoing endovascular aneurysm repair.

BACKGROUND: Endovascular aneurysm repair (EVAR) for abdominal aortic aneurysm (AAA) is associated with risks such as endoleaks and late aneurysm ruptu...

AI-Guided Patient-Derived Endothelial Modeling Identifies a Reversible Moyamoya-Specific miRNA Deficiency Corrected by Stem Cell-Extracellular Vesicles.

Moyamoya disease (MMD) is a progressive cerebrovascular disorder characterized by abnormal vascular remodeling and impaired angiogenesis. We profiled ...

Slow-wave-modulated high-frequency oscillations reveal early network abnormalities in pre-pathological 5XFAD mice.

Alzheimer's disease (AD) is characterized by progressive disruption of large-scale neural networks, leading to abnormal brain oscillatory activity, ye...

Extracranial vascular association of moyamoya disease: a systematic review and machine learning analysis.

BACKGROUND: Intracranial steno-occlusive lesions are characteristic of moyamoya disease (MMD), but increasing reports of extracranial vascular involve...

Peripheral and central immune features in insomnia: Integrative bulk and single-cell transcriptomic analyses reveal core hub genes and candidate compounds.

Insomnia is closely associated with immune dysregulation, yet the overall pattern of peripheral-central immune disequilibrium and its underlying molec...