Cardiovascular

Atherosclerosis

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

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Cardiovascular disease detection using machine learning and carotid/femoral arterial imaging frameworks in rheumatoid arthritis patients.

The study proposes a novel machine learning (ML) paradigm for cardiovascular disease (CVD) detection...

Using Machine Learning to Evaluate the Role of Microinflammation in Cardiovascular Events in Patients With Chronic Kidney Disease.

BACKGROUND: Lipid metabolism disorder, as one major complication in patients with chronic kidney dis...

Deep Learning to Automatically Segment and Analyze Abdominal Aortic Aneurysm from Computed Tomography Angiography.

PURPOSE: Although segmentation of Abdominal Aortic Aneurysms (AAA) thrombus is a crucial step for bo...

Applications of Artificial Intelligence in Non-cardiac Vascular Diseases: A Bibliographic Analysis.

Research output related to artificial intelligence (AI) in vascular diseases has been poorly investi...

Artificial intelligence approaches to the determinants of women's vaginal dryness using general hospital data.

The aim of this study is to analyse the determinants of women's vaginal dryness using machine learni...

Computational identification of 4-carboxyglutamate sites to supplement physiological studies using deep learning.

In biological systems, Glutamic acid is a crucial amino acid which is used in protein biosynthesis. ...

OnePetri: Accelerating Common Bacteriophage Petri Dish Assays with Computer Vision.

Bacteriophage plaque enumeration is a critical step in a wide array of protocols. The current gold ...

A hybrid deep learning paradigm for carotid plaque tissue characterization and its validation in multicenter cohorts using a supercomputer framework.

BACKGROUND: Early and automated detection of carotid plaques prevents strokes, which are the second ...

Change patterns in the corneal sub-basal nerve and corneal aberrations in patients with dry eye disease: An artificial intelligence analysis.

We aimed to investigate the change patterns in corneal sub-basal nerve morphology and corneal intrin...

Weakly Supervised Sensitive Heatmap framework to classify and localize diabetic retinopathy lesions.

Vision loss happens due to diabetic retinopathy (DR) in severe stages. Thus, an automatic detection ...

A machine learning pipeline revealing heterogeneous responses to drug perturbations on vascular smooth muscle cell spheroid morphology and formation.

Machine learning approaches have shown great promise in biology and medicine discovering hidden info...

Integrating deep learning with microfluidics for biophysical classification of sickle red blood cells adhered to laminin.

Sickle cell disease, a genetic disorder affecting a sizeable global demographic, manifests in sickle...

Deep learning enables genetic analysis of the human thoracic aorta.

Enlargement or aneurysm of the aorta predisposes to dissection, an important cause of sudden death. ...

Radiation dose reduction with deep-learning image reconstruction for coronary computed tomography angiography.

OBJECTIVES: Deep-learning image reconstruction (DLIR) offers unique opportunities for reducing image...

Generation of Interconnected Neural Clusters in Multiscale Scaffolds from Human-Induced Pluripotent Stem Cells.

The development of in vitro neural networks depends to a large extent on the scaffold properties, in...

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