Cardiovascular

Atherosclerosis

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

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A Deep Learning Approach to Visualize Aortic Aneurysm Morphology Without the Use of Intravenous Contrast Agents.

BACKGROUND: Intravenous contrast agents are routinely used in CT imaging to enable the visualization...

Deep Learning on Multiphysical Features and Hemodynamic Modeling for Abdominal Aortic Aneurysm Growth Prediction.

Prediction of abdominal aortic aneurysm (AAA) growth is of essential importance for the early treatm...

Mechano-fluorescence actuation in single synaptic vesicles with a DNA framework nanomachine.

Biomimetic machines that can convert mechanical actuation to adaptive coloration in a manner analogo...

Automatic lesion detection and segmentation in F-flutemetamol positron emission tomography images using deep learning.

BACKGROUND: Beta amyloid in the brain, which was originally confirmed by post-mortem examinations, c...

Artificial intelligence-driven identification of morin analogues acting as Ca1.2 channel blockers: Synthesis and biological evaluation.

Morin is a vasorelaxant flavonoid, whose activity is ascribable to Ca1.2 channel blockade that, howe...

Deep learning based on carotid transverse B-mode scan videos for the diagnosis of carotid plaque: a prospective multicenter study.

OBJECTIVES: Accurate detection of carotid plaque using ultrasound (US) is essential for preventing s...

Mobile-CellNet: Automatic Segmentation of Corneal Endothelium Using an Efficient Hybrid Deep Learning Model.

PURPOSE: The corneal endothelium, the innermost layer of the human cornea, exhibits a morphology of ...

Efficient targeted learning of heterogeneous treatment effects for multiple subgroups.

In biomedical science, analyzing treatment effect heterogeneity plays an essential role in assisting...

Deep learning-based noise reduction for coronary CT angiography: using four-dimensional noise-reduction images as the ground truth.

BACKGROUND: To assess low-contrast areas such as plaque and coronary artery stenosis, coronary compu...

Patch-based CNN for corneal segmentation of AS-OCT images: Effect of the number of classes and image quality upon performance.

Anterior segment optical coherence tomography (AS-OCT) is a fundamental ophthalmic imaging technique...

Aortic Distensibility Measured by Automated Analysis of Magnetic Resonance Imaging Predicts Adverse Cardiovascular Events in UK Biobank.

Background Automated analysis of cardiovascular magnetic resonance images provides the potential to ...

Machine learning for outcome prediction of neurosurgical aneurysm treatment: Current methods and future directions.

INTRODUCTION: Machine learning algorithms have received increased attention in neurosurgical literat...

Finding the influential clinical traits that impact on the diagnosis of heart disease using statistical and machine-learning techniques.

In recent years, the omnipresence of cardiac problems has been recognized as an epidemic. With the c...

Detection of cerebral aneurysms using artificial intelligence: a systematic review and meta-analysis.

BACKGROUND: Subarachnoid hemorrhage from cerebral aneurysm rupture is a major cause of morbidity and...

Robot-Assisted Surgery of an Iliac Artery Aneurysm: A Case Report.

Robot-assisted surgery has not yet been able to establish itself for vascular surgery. However, the ...

Gene-gene interaction detection with deep learning.

The extent to which genetic interactions affect observed phenotypes is generally unknown because cur...

Successful implementation of a nurse-navigator-run program using natural language processing identifying patients with an abdominal aortic aneurysm.

BACKGROUND: Abdominal aortic aneurysms (AAA) are often identified incidentally on imaging studies. P...

[Future of interventional cardiology : Does everything revolve around AI and robotics?].

In recent years, software-assisted imaging systems, such as computed tomography, have contributed to...

Magnetic torque-driven living microrobots for increased tumor infiltration.

Biohybrid bacteria-based microrobots are increasingly recognized as promising externally controllabl...

Using modern risk engines and machine learning/artificial intelligence to predict diabetes complications: A focus on the BRAVO model.

Management of diabetes requires a multifaceted approach of risk factor reduction; through management...

Development of non-bias phenotypic drug screening for cardiomyocyte hypertrophy by image segmentation using deep learning.

The number of patients with heart failure and related deaths is rapidly increasing worldwide, making...

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