Atherosclerosis

Revolutionizing Aneurysm detection: The role of artificial intelligence in reducing rupture rates.

Cerebral aneurysms, affecting 2-5% of the global population, are often asymptomatic and commonly located within the Circle of Willis. A recent study in Neurosurgical Review highlights a significant reduction in the annual rupture rates of unruptured cerebral aneurysms (UCAs) in Japan from 2003 to 2018. By analyzing age-adjusted mortality rates of subarachnoid hemorrhage (SAH) and the number of tre...

A comprehensive multi-task deep learning approach for predicting metabolic syndrome with genetic, nutritional, and clinical data.

Metabolic syndrome (MetS) is a complex disorder characterized by a cluster of metabolic abnormalities, including abdominal obesity, hypertension, elevated triglycerides, reduced high-density lipoprotein cholesterol, and impaired glucose tolerance. It poses a significant public health concern, as individuals with MetS are at an increased risk of developing cardiovascular diseases and type 2 diabete...

Deep Learning Based Automatic Segmentation of the Thoracic Aorta from Chest Computed Tomography in Healthy Korean Adults.

OBJECTIVE: Segmenting the aorta into zones based on anatomical landmarks is a current trend to better understand interventions for aortic dissection o...

Off-Label use of Woven EndoBridge device for intracranial brain aneurysm treatment: Modeling of occlusion outcome.

INTRODUCTION: The Woven EndoBridge (WEB) device is emerging as a novel therapy for intracranial aneurysms, but its use for off-label indications requi...

Deep learning for intracranial aneurysm segmentation using CT angiography.

This study aimed to employ a two-stage deep learning method to accurately detect small aneurysms (4-10 mm in size) in computed tomography angiography ...

Potential Shared Mitochondrial-Related Gene Signatures and Molecular Mechanisms Between Polycystic Ovary Syndrome (PCOS) and Major Depressive Disorder (MDD): Evidence from Transcriptome Data and Machine Learning.

Polycystic ovary syndrome (PCOS) is strongly associated with major depressive disorder (MDD), but the shared pathophysiological mechanisms between the...

A stacking ensemble model for predicting the occurrence of carotid atherosclerosis.

BACKGROUND: Carotid atherosclerosis (CAS) is a significant risk factor for cardio-cerebrovascular events. The objective of this study is to employ sta...

Logistic Regression and Statistical Regularization Techniques for Risk Classification of Coronary Artery Disease using Cytokines transported by high density lipoproteins.

Coronary artery disease (CAD) is a leading cause of mortality in the world. It is important to be able to proactively assess the risk of the disease, ...

Optimization of Smoking Classification by Applying Neural Network with Variable Importance Using Cytokine Biomarkers.

Cigarette smoking is a preventable epidemic that is a leading cause of death. It increases the risk of coronary heart disease, stroke, lung cancer, ch...

A novel optimization-assisted multi-scale and dilated adaptive hybrid deep learning network with feature fusion for event detection from social media.

Social media networks become an active communication medium for connecting people and delivering new messages. Social media can perform as the primary...

In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy.

Due to considerable global prevalence and high recurrence rate, the pursuit of effective new medication for epilepsy treatment remains an urgent and s...

A machine learning algorithm for stratification of risk of cardiovascular disease in metabolic dysfunction-associated steatotic liver disease.

BACKGROUND: Steatotic liver disease (SLD) is associated with adverse cardiac events. Metabolic dysfunction-associated steatotic liver disease (MASLD) ...

Unsupervised shape-and-texture-based generative adversarial tuning of pre-trained networks for carotid segmentation from 3D ultrasound images.

BACKGROUND: Vessel-wall volume and localized three-dimensional ultrasound (3DUS) metrics are sensitive to the change of carotid atherosclerosis in res...

Efficient segmentation of active and inactive plaques in FLAIR-images using DeepLabV3Plus SE with efficientnetb0 backbone in multiple sclerosis.

This research paper introduces an efficient approach for the segmentation of active and inactive plaques within Fluid-attenuated inversion recovery (F...

Automated Method for Intracranial Aneurysm Classification Using Deep Learning.

Intracranial aneurysm (IA) is now a common term closely associated with subarachnoid hemorrhage. IA is the bulging of a blood vessel caused by a weake...

Assessing accuracy and consistency in intracranial aneurysm sizing: human expertise vs. artificial intelligence.

Intracranial aneurysms (IAs) are a common vascular pathology and are associated with a risk of rupture, which is often fatal. Aneurysm growth of more ...

Molecular docking aided machine learning for the identification of potential VEGFR inhibitors against renal cell carcinoma.

Renal cell carcinoma is a highly vascular tumor associated with vascular endothelial growth factor (VEGF) expression. The Vascular Endothelial Growth ...

A comprehensive investigation of morphological features responsible for cerebral aneurysm rupture using machine learning.

Cerebral aneurysms are a silent yet prevalent condition that affects a significant global population. Their development can be attributed to various f...

Predicting blood-brain barrier permeability of molecules with a large language model and machine learning.

Predicting the blood-brain barrier (BBB) permeability of small-molecule compounds using a novel artificial intelligence platform is necessary for drug...

Artificial intelligence-driven multiomics predictive model for abdominal aortic aneurysm subtypes to identify heterogeneous immune cell infiltration and predict disease progression.

BACKGROUND: Abdominal aortic aneurysm (AAA) poses a significant health risk and is influenced by various compositional features. This study aimed to d...