Peripheral Artery Disease

Decoding the Genetic Architecture of Acute Coronary Syndrome: A Review on Integrated Medical Modeling.

UNLABELLED: Genetic mutations contribute significantly to the complexity of understanding Acute Coronary Syndrome (ACS). Artificial Intelligence (AI) models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN), have been integrated as an advanced approach to uncover hidden mutation clues for early detection and prevention of life-thr...

Super learner model for predicting carotid plaque regression in type 2 diabetes on PCSK9 inhibitors.

OBJECTIVES: Evidence regarding the effects of proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors on carotid plaque regression in patients with type 2 diabetes mellitus (T2DM) and subclinical atherosclerosis remains limited; therefore, this study aimed to develop and validate a machine learning-based model for predicting carotid plaque regression in this population. METHODS: This retr...

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study.

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage increases risk of vascular events...

Identifying Patients at Elevated Risk of Stroke After.

BACKGROUND: Transcarotid artery revascularization (TCAR) has assumed a significant role in the surgical treatment of extracranial carotid occlusive di...

A machine learning-based framework for predicting hypertension using serum hematological factors.

Hypertension (HTN) is a leading global cause of cardiovascular disease (CVD) and all-cause mortality, underscoring the need for early detection and in...

Decoding chromatin regulator-LAIR1+ M2 like macrophage patterns in atherosclerosis and clinical outcomes of Lung adenocarcinoma patients: evidence from artificial intelligence-driven multi omics and in vitro validation.

Atherosclerosis (AS) is a common complication of lung adenocarcinoma (LUAD), but its underlying mechanisms in LUAD remain unclear. This study aimed to...

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 hetero...

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 d...

Rapid screening of spreading-type Bacillus using a YOLO-based classifier on sheet media.

Aerobic spore-forming bacteria cause food poisoning and spoilage and can be distinguished from other bacteria based on colony size and shape when grow...

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...

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...

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...

Predicting Intramyocardial Hemorrhage Before Reperfusion in STEMI Patients With Intrinsically Explainable Artificial Intelligence.

BACKGROUND: Intramyocardial hemorrhage (IMH) complicates approximately 40% of reperfused ST-segment elevation myocardial infarctions (STEMIs) and is a...

Re: "A Dynamic Machine Learning Approach to Complement Nurse-Led Clinics in Identifying High-Risk Patients with Intermittent Claudication".

Streetview greenspace types and dementia risk in older adults: The Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Greenspace has been associated with lower dementia risk but most studies have used satellite-derived measures that cannot distinguish vege...

Combinations of single gene predictors with AI-driven polygenic precision therapies in cardiovascular diseases.

Pharmacogenomics (PGx) is transforming how we treat cardiovascular disease (CVD) by enabling us to select and dose drugs based on our genetic profiles...

Hybrid vision transformer and ensemble machine learning framework for automated atherosclerotic plaque classification in intravascular ultrasound imaging.

Atherosclerotic plaque classification in intravascular ultrasound (IVUS) imaging is crucial for cardiovascular disease diagnosis and treatment plannin...

Research progress on methods for determining monosaccharide composition and its relationship with activities: A review.

Polysaccharides are one of the most abundant biomacromolecules in nature and serve as the key material basis for the therapeutic effects of traditiona...

The emerging role of coronary computed tomography for prevention of cardiovascular disease in asymptomatic individuals.

The persistent global rise in atherosclerotic cardiovascular disease (ASCVD) challenges the effectiveness of current risk factor-based algorithms in p...