Atherosclerosis

Towards a new model and classification of mood disorders based on risk resilience, neuro-affective toxicity, staging, and phenome features using the nomothetic network psychiatry approach.

Current diagnoses of mood disorders are not cross validated. The aim of the current paper is to expl...

Evidence of vascular endothelial dysfunction in Wooden Breast disorder in chickens: Insights through gene expression analysis, ultra-structural evaluation and supervised machine learning methods.

Several gene expression studies have been previously conducted to characterize molecular basis of Wo...

Porphyrin-based covalent organic framework as bioplatfrom for detection of vascular endothelial growth factor 165 through fluorescence resonance energy transfer.

A fluorescent aptasensor based on porphyrin-based covalent organic framework (p-COF) and carbon dots...

Predictive value of triglyceride/high-density lipoprotein cholesterol for major clinical outcomes in advanced chronic kidney disease: a nationwide population-based study.

BACKGROUND: Dyslipidemia is an essential parameter in the prediction of cardiovascular disease (CVD)...

Characterization of Antiphospholipid Syndrome Atherothrombotic Risk by Unsupervised Integrated Transcriptomic Analyses.

OBJECTIVE: Our aim was to characterize distinctive clinical antiphospholipid syndrome phenotypes and...

Prognostic Biomarkers for Thrombotic Microangiopathy after Acute Graft-versus-Host Disease: A Nested Case-Control Study.

Transplantation-associated thrombotic microangiopathy (TA-TMA) is a complication of allogeneic hemat...

Artificial Intelligence in Coronary Computed Tomography Angiography: From Anatomy to Prognosis.

Cardiac computed tomography angiography (CCTA) is widely used as a diagnostic tool for evaluation of...

Development of a quantitative systems pharmacology model of chronic kidney disease: metabolic bone disorder.

Chronic kidney disease mineral bone disorder (CKD-MBD) is a virtually universal complication of kidn...

Fully automated detection and segmentation of intracranial aneurysms in subarachnoid hemorrhage on CTA using deep learning.

In aneurysmal subarachnoid hemorrhage (aSAH), accurate diagnosis of aneurysm is essential for subseq...

Fully automatic volume segmentation of infrarenal abdominal aortic aneurysm computed tomography images with deep learning approaches versus physician controlled manual segmentation.

OBJECTIVE: Imaging software has become critical tools in the diagnosis and decision making for the t...

Trace element, immune and opioid biomarkers of unstable angina, increased atherogenicity and insulin resistance: Results of machine learning.

BACKGROUND: Aberrations in endothelial cells, immune and oxidative pathways are associated with athe...

PWD-3DNet: A Deep Learning-Based Fully-Automated Segmentation of Multiple Structures on Temporal Bone CT Scans.

The temporal bone is a part of the lateral skull surface that contains organs responsible for hearin...

Deep Learning-Based Detection of Endothelial Tip Cells in the Oxygen-Induced Retinopathy Model.

Proliferative retinopathies, such as diabetic retinopathy and retinopathy of prematurity, are leadin...

The impact of anticoagulant and antiplatelet drugs therapy on perioperative outcomes of purely off-clamp robot-assisted partial nephrectomy: a single-center experience.

A clinically applicable deep-learning model for detecting intracranial aneurysm in computed tomography angiography images.

Intracranial aneurysm is a common life-threatening disease. Computed tomography angiography is recom...

Intravenous iron therapy and the cardiovascular system: risks and benefits.

Anaemia is a common complication of chronic kidney disease (CKD). In this setting, iron deficiency i...

A new deep learning method for displacement tracking from ultrasound RF signals of vascular walls.

It is necessary to monitor the mechanical properties of arteries which directly related to cardiovas...

Predictive score for complete occlusion of intracranial aneurysms treated by flow-diverter stents using machine learning.

BACKGROUND: Complete occlusion of an intracranial aneurysm (IA) after the deployment of a flow-diver...

Multiclass machine learning vs. conventional calculators for stroke/CVD risk assessment using carotid plaque predictors with coronary angiography scores as gold standard: a 500 participants study.

Machine learning (ML)-based algorithms for cardiovascular disease (CVD) risk assessment have shown p...

Deep Learning for Detecting Cerebral Aneurysms with CT Angiography.

Background Cerebral aneurysm detection is a challenging task. Deep learning may become a supportive ...

Automated Aneurysm Detection: Emerging from the Shallow End of the Deep Learning Pool.