Cardiovascular

Atherosclerosis

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

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Semi-Automated Data Curation from Biomedical Literature.

Data curation is a bottleneck for many informatics pipelines. A specific example of this is aggregat...

Development and validation of a deep learning model for prediction of intracranial aneurysm rupture risk based on multi-omics factor.

OBJECTIVE: The clinical ability of radiomics to predict intracranial aneurysm rupture risk remains u...

Can convolutional neural networks identify external carotid artery calcifications?

OBJECTIVE: We developed and evaluated the accuracy and reliability of a convolutional neural network...

Interpretable attention-based deep learning ensemble for personalized ovarian cancer treatment without manual annotations.

Inhibition of pathological angiogenesis has become one of the first FDA approved targeted therapies ...

Optimizing multi-domain hematologic biomarkers and clinical features for the differential diagnosis of unipolar depression and bipolar depression.

There is a lack of objective features for the differential diagnosis of unipolar and bipolar depress...

How will artificial intelligence transform cardiovascular computed tomography? A conversation with an AI model.

Artificial intelligence (AI) has the potential to transform healthcare, but its clinical use also ha...

Coupling analysis of heart rate variability and cortical arousal using a deep learning algorithm.

Frequent cortical arousal is associated with cardiovascular dysfunction among people with sleep-diso...

Identifying Reasons for Statin Nonuse in Patients With Diabetes Using Deep Learning of Electronic Health Records.

Background Statins are guideline-recommended medications that reduce cardiovascular events in patien...

A genome-wide association study of childhood adiposity and blood lipids.

The rising prevalence of childhood obesity and dyslipidaemia is a major public health concern due t...

Multi-mode information fusion navigation system for robot-assisted vascular interventional surgery.

BACKGROUND: Minimally invasive vascular intervention (MIVI) is a powerful technique for the treatmen...

Deep Learning for Head and Neck CT Angiography: Stenosis and Plaque Classification.

Background Studies have rarely investigated stenosis detection from head and neck CT angiography sca...

Automated in-depth cerebral arterial labelling using cerebrovascular vasculature reframing and deep neural networks.

Identifying the cerebral arterial branches is essential for undertaking a computational approach to ...

Increasing transparency in machine learning through bootstrap simulation and shapely additive explanations.

Machine learning methods are widely used within the medical field. However, the reliability and effi...

Segmentation of the aorta in systolic phase from 4D flow MRI: multi-atlas vs. deep learning.

OBJECTIVE: In the management of the aortic aneurysm, 4D flow magnetic resonance Imaging provides val...

A Deep Learning Approach for Automated Bone Removal from Computed Tomography Angiography of the Brain.

Advanced visualization techniques such as maximum intensity projection (MIP) and volume rendering (V...

Adaptive fuzzy control of drug delivery in cancer treatment using combination of chemotherapy and antiangiogenic therapy.

This paper introduces the adaptive fuzzy control scheme as a promising control technique for cancer ...

Diagnosis of coronary layered plaque by deep learning.

Healed coronary plaques, morphologically characterized by a layered phenotype, are signs of previous...

High-throughput 3DRA segmentation of brain vasculature and aneurysms using deep learning.

BACKGROUND AND OBJECTIVES: Automatic segmentation of the cerebral vasculature and aneurysms facilita...

Deep learning-based semantic vessel graph extraction for intracranial aneurysm rupture risk management.

PURPOSE: Intracranial aneurysms are vascular deformations in the brain which are complicated to trea...

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