Atherosclerosis

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...

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 medicat...

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 dysfu...

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 sensiti...

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 pla...

Automated Method for Intracranial Aneurysm Classification Using Deep Learning.

Intracranial aneurysm (IA) is now a common term closely associated with subarachnoid hemorrhage. IA ...

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 ruptu...

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 arti...

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...

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 (...

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 var...

Machine Learning Based Prediction of Post-operative Infrarenal Endograft Apposition for Abdominal Aortic Aneurysms.

OBJECTIVE: Challenging infrarenal aortic neck characteristics have been associated with an increased...

Potentials of artificial intelligence in familial hypercholesterolemia: Advances in screening, diagnosis, and risk stratification for early intervention and treatment.

Familial hypercholesterolemia (FH) poses a global health challenge due to high incidence rates and u...

Explainable artificial intelligence for LDL cholesterol prediction and classification.

INTRODUCTION: Monitoring LDL-C levels is essential in clinical practice because there is a direct re...

Artificial intelligence-based evaluation of carotid artery compressibility via point-of-care ultrasound in determining the return of spontaneous circulation during cardiopulmonary resuscitation.

AIM: This study introduces RealCAC-Net, an artificial intelligence (AI) system, to quantify carotid ...

Evaluation of Serum Visfatin as a Biomarker of Lupus Nephritis in Egyptian Patients with Systemic Lupus Erythematosus.

One of the most significant consequences of systemic lupus erythematosus (SLE) is lupus nephritis (L...

Classification, detection, and segmentation performance of image-based AI in intracranial aneurysm: a systematic review.

BACKGROUND: The detection and management of intracranial aneurysms (IAs) are vital to prevent life-t...

Evaluation of Dental Plaque Area with Artificial Intelligence Model.

OBJECTIVES: This study aims to assess the diagnostic accuracy of an artificial intelligence (AI) sys...

Temporal Convolutional Neural Network-Based Prediction of Vascular Health in Elderly Women Using Photoplethysmography-Derived Pulse Wave during Exercise.

(1) Background: The objective of this study was to predict the vascular health status of elderly wom...

Artificial Intelligence Based Methods to Enhance Analysis of Non-Contrast Computed Tomography in Patients with Aortic Aneurysm.

Integrated analysis of single-cell sequencing and machine learning identifies a signature based on monocyte/macrophage hub genes to analyze the intracranial aneurysm associated immune microenvironment.

Monocytes are pivotal immune cells in eliciting specific immune responses and can exert a significan...