Cardiovascular

Atherosclerosis

Latest AI and machine learning research in atherosclerosis for healthcare professionals.

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Machine learning reveals serum sphingolipids as cholesterol-independent biomarkers of coronary artery disease.

BACKGROUNDCeramides are sphingolipids that play causative roles in diabetes and heart disease, with ...

A Deep Learning Approach in Rebubbling After Descemet's Membrane Endothelial Keratoplasty.

PURPOSE: To evaluate the efficacy of deep learning in judging the need for rebubbling after Descemet...

Deep learning predicts function of live retinal pigment epithelium from quantitative microscopy.

Increases in the number of cell therapies in the preclinical and clinical phases have prompted the n...

Therapeutic approach comparison in bicuspid aortic valve aortopathy and clinical practice implications.

Bicuspid aortic valve (BAV) is the most common heart valve malformation, and it may be associated wi...

[Innovative activated platelet detection technology by artificial intelligence].

Although antiplatelet drugs are widely used for the prevention and treatment of atherothrombosis, cl...

Deep Learning for Carotid Plaque Segmentation using a Dilated U-Net Architecture.

Carotid plaque segmentation in ultrasound longitudinal B-mode images using deep learning is presente...

Application of Artificial Intelligence in Targeting Retinal Diseases.

Retinal diseases affect an increasing number of patients worldwide because of the aging population. ...

Detection of Disease-Specific Parent Cells Via Distinct Population of Nano-Vesicles by Machine Learning.

BACKGROUND: The diagnosis and prognosis of pathological conditions, such as age-related macular dege...

Potassium selenocyanoacetate reduces the blood triacylglycerol and atherosclerotic plaques in high-fat-dieted mice.

BACKGROUND: Controlling blood lipid levels at the early stage of cardiovascular disease is a major f...

Motion-compensated frame rate up-conversion in carotid ultrasound images using optical flow and manifold learning.

OBJECTIVE: Carotid ultrasonography is a reliable and non-invasive method to evaluate atherosclerosis...

Ex-vivo antihypertensive and calcium channel blocking activity of Androsace foliosa n-hexane leaves fraction on isolated rabbit aorta.

Hypertension is persistent elevation in blood pressure for 3-4 weeks. Estimated global prevalence of...

Automated A-line coronary plaque classification of intravascular optical coherence tomography images using handcrafted features and large datasets.

We developed machine learning methods to identify fibrolipidic and fibrocalcific A-lines in intravas...

Convolutional Neural Networks for the Detection and Measurement of Cerebral Aneurysms on Magnetic Resonance Angiography.

Aneurysm size correlates with rupture risk and is important for treatment planning. User annotation ...

Optical Coherence Tomography Vulnerable Plaque Segmentation Based on Deep Residual U-Net.

Automatic and accurate segmentation of intravascular optical coherence tomography imagery is of grea...

Representation Learning of 3D Brain Angiograms, an Application for Cerebral Vasospasm Prediction.

Stroke is the fifth leading cause of death in the United States. Subarachnoid hemorrhage (SAH) is a ...

Predicting Gastrointestinal Bleeding Events from Multimodal In-Hospital Electronic Health Records Using Deep Fusion Networks.

Applying machine learning (ML) methods on electronic health records (EHRs) that accurately predict t...

Automated Ultrasound Doppler Angle Estimation Using Deep Learning.

Angle estimation is an important step in the Doppler ultrasound clinical workflow to measure blood v...

Integrating Active Learning and Transfer Learning for Carotid Intima-Media Thickness Video Interpretation.

Cardiovascular disease (CVD) is the number one killer in the USA, yet it is largely preventable (Wor...

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