Cardiovascular

Peripheral Artery Disease

Latest AI and machine learning research in peripheral artery disease for healthcare professionals.

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Showing 463-483 of 7,581 articles
Machine learning using scRNA-seq Combined with bulk-seq to identify lactylation-related hub genes in carotid arteriosclerosis.

Atherosclerosis is a chronic inflammatory disease, this study aims to investigate the immune landsca...

Recognizing artery segments on carotid ultrasonography using embedding concatenation of deep image and vision-language models.

Evaluating large artery atherosclerosis is critical for predicting and preventing ischemic strokes. ...

Diagnostic value of small dense low-density lipoprotein and trace elements in coronary artery disease.

Coronary artery disease (CAD) is a worldwide leading cause of death. Considering that 20%-40% of pat...

Detection of carotid artery calcifications using artificial intelligence in dental radiographs: a systematic review and meta-analysis.

BACKGROUND: Carotid artery calcifications are important markers of cardiovascular health, often asso...

Comparative Performance of Clinician and Computational Approaches in Forecasting Adverse Outcomes in Intermittent Claudication.

BACKGROUND: Recent evidence has shown that machine learning (ML) techniques can accurately forecast ...

Acute coronary syndromes: mechanisms, challenges, and new opportunities.

Despite advances in research and patient management, atherosclerosis and its dreaded acute and chron...

A deep learning and molecular modeling approach to repurposing Cangrelor as a potential inhibitor of Nipah virus.

Deforestation, urbanization, and climate change have significantly increased the risk of zoonotic di...

Eliciting the Impact of Metformin and Statins on Prostate Cancer Outcomes from a Real-life National Database Analysis.

Several large analyses have revealed contradictory results regarding the association between prostat...

Shortcut learning leads to sex bias in deep learning models for photoacoustic tomography.

PURPOSE: Shortcut learning has been identified as a source of algorithmic unfairness in medical imag...

Identification of Novel Diagnostic Markers for Atherosclerosis Using Machine-Learning Algorithms.

OBJECTIVE: To outline immune-cell infiltration and identify diagnostic genes for atherosclerosis (AS...

[Coronary computed tomography in the clinical arena. Recent evidence and future perspectives].

In the past few years, computed tomography coronary angiography (CTCA) has rapidly become a widely u...

Repurposing FDA-approved drugs as NLRP3 inhibitors against inflammatory diseases: machine learning and molecular simulation approaches.

Activation of NLRP3 (NOD-like receptor family, pyrin domain-containing protein 3) has been associate...

Deep Learning-based Brain Age Prediction Using MRI to Identify Fetuses with Cerebral Ventriculomegaly.

Fetal ventriculomegaly (VM) and its severity and associated central nervous system (CNS) abnormaliti...

A psychologically interpretable artificial intelligence framework for the screening of loneliness, depression, and anxiety.

Negative emotions such as loneliness, depression, and anxiety (LDA) are prevalent and pose significa...

The multikinetic fusion feature of PPG was combined with MCNN_vision_transformer for diabetes detection.

BACKGROUND: Diabetes is a chronic condition that significantly impacts the cardiovascular system and...

ML-ROM wall shear stress prediction in patient-specific vascular pathologies under a limited clinical training data regime.

High-fidelity numerical simulations such as Computational Fluid Dynamics (CFD) have been proven effe...

: Scanner-based image acquisition of medically important arthropods for the development of computer vision and deep learning models.

Computer vision methods offer great potential for rapid image-based identification of medically impo...

Toward clearer recognition and easier usefulness: development of a cross-lingual atherosclerotic cerebrovascular disease ontology.

Atherosclerotic cerebrovascular disease could result in a great number of deaths and disabilities. H...

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