Atherosclerosis

The Bioprotective Effects of Marigold Tea Polyphenols on Obesity and Oxidative Stress Biomarkers in High-Fat-Sugar Diet-Fed Rats.

The research is aimed at exploring the potential of marigold petal tea (MPT), rich in polyphenol contents, against oxidative stress and obesity in a rat model following a high-fat-sugar diet (HFSD). The MPT was prepared through the customary method of decoction and was subjected to analysis for its polyphenol composition using reversed-phase high-performance liquid chromatography (RP-HPLC). Two ...

Predicting Individual Treatment Effects to Determine Duration of Dual Antiplatelet Therapy After Stent Implantation.

BACKGROUND: After coronary stent implantation, prolonged dual antiplatelet therapy (DAPT) increases bleeding risk, requiring personalization of DAPT duration. The aim of this study was to develop and validate a machine learning model to predict optimal DAPT duration after contemporary drug-eluting stent implantation in patients with coronary artery disease.

Patient-Specific Myocardial Infarction Risk Thresholds From AI-Enabled Coronary Plaque Analysis.

BACKGROUND: Plaque quantification from coronary computed tomography angiography has emerged as a valuable predictor of cardiovascular risk. Deep learn...

Graphene Microelectrode Arrays, 4D Structured Illumination Microscopy, and a Machine Learning Spike Sorting Algorithm Permit the Analysis of Ultrastructural Neuronal Changes During Neuronal Signaling in a Model of Niemann-Pick Disease Type C.

Simultaneously recording network activity and ultrastructural changes of the synapse is essential for advancing understanding of the basis of neuronal...

Deep learning-based binary classification of beta-amyloid plaques using 18 F florapronol PET.

PURPOSE: This study aimed to investigate a deep learning model to classify amyloid plaque deposition in the brain PET images of patients suspected of ...

Detection of cardiovascular disease cases using advanced tree-based machine learning algorithms.

Cardiovascular disease (CVD) can often lead to serious consequences such as death or disability. This study aims to identify a tree-based machine lear...

Determination of spectroscopy marker of atherosclerotic carotid stenosis using FTIR-ATR combined with machine learning and chemometrics analyses.

Atherosclerotic carotid stenosis (ACS) is a recognized risk factor for ischemic stroke. Currently, the gold diagnostic standard is Doppler ultrasound,...

In Silico Modeling of Fabry Disease Pathophysiology for the Identification of Early Cellular Damage Biomarker Candidates.

Fabry disease (FD) is an X-linked lysosomal disease whose ultimate consequences are the accumulation of sphingolipids and subsequent inflammatory even...

Raman spectroscopy combined with machine learning and chemometrics analyses as a tool for identification atherosclerotic carotid stenosis from serum.

Atherosclerosis carotid stenosis (ACS) is one of the main causes of stroke. Unfortunately, the highest number of people go to the doctor with an advan...

Enhanced Plaque Stabilization Effects of Alirocumab　- Insights From Artificial Intelligence-Aided Optical Coherence Tomography Analysis of the Alirocumab for Thin-Cap Fibroatheroma in Patients With Coronary Artery Disease Estimated by Optical Coherence Tomography (ALTAIR) Study.

BACKGROUND: Proprotein convertase subtilisin/kexin type 9 inhibitors stabilize vulnerable plaque, reducing cardiovascular events. However, manual opti...

DeepPlaq: Dental plaque indexing based on deep neural networks.

OBJECTIVES: The selection of treatment for dental plaque is closely related to the condition of the plaque on different teeth. This study validated th...

Automated diagnosis of atherosclerosis using multi-layer ensemble models and bio-inspired optimization in intravascular ultrasound imaging.

Atherosclerosis causes heart disease by forming plaques in arterial walls. IVUS imaging provides a high-resolution cross-sectional view of coronary ar...

Advancements in opportunistic intracranial aneurysm screening: The impact of a deep learning algorithm on radiologists' analysis of T2-weighted cranial MRI.

(1) Background: Unruptured Intracranial Aneurysms (UIAs) are common blood vessel malformations, occurring in up to 3 % of healthy adults. Magnetic Res...

Development and validation of cardiometabolic risk predictive models based on LDL oxidation and candidate geromarkers from the MARK-AGE data.

The predictive value of the susceptibility to oxidation of LDL particles (LDLox) in cardiometabolic risk assessment is incompletely understood. The ma...

Clinical impact of deep learning-derived intravascular ultrasound characteristics in patients with deferred coronary artery.

Prognostic markers for long-term outcomes are lacking in patients with deferred (nonculprit) coronary artery lesions. This study aimed to identify the...

Plasma cell-free RNA signatures of inflammatory syndromes in children.

Inflammatory syndromes, including those caused by infection, are a major cause of hospital admissions among children and are often misdiagnosed becaus...

Long-term Major Adverse Cardiac Event Prediction by Computed Tomography-derived Plaque Measures and Clinical Parameters Using Machine Learning.

Objective The present study evaluated the usefulness of machine learning (ML) models with the coronary computed tomography imaging and clinical parame...

Artificial intelligence can help detecting incidental intracranial aneurysm on routine brain MRI using TOF MRA data sets and improve the time required for analysis of these images.

PURPOSE: The aim of our study was to assess the diagnostic performance of commercially available AI software for intracranial aneurysm detection and t...

Volume Measurements for Surveillance after Endovascular Aneurysm Repair using Artificial Intelligence.

OBJECTIVE: Surveillance after endovascular aneurysm repair (EVAR) is suboptimal due to limited compliance and relatively large variability in measurem...

A Scoping Review of Machine-Learning Derived Radiomic Analysis of CT and PET Imaging to Investigate Atherosclerotic Cardiovascular Disease.

BACKGROUND: Cardiovascular disease affects the carotid arteries, coronary arteries, aorta and the peripheral arteries. Radiomics involves the extracti...