Atherosclerosis

Mechanisms of QingRe HuoXue Formula in atherosclerosis Treatment: An integrated approach using Bioinformatics, Machine Learning, and experimental validation.

BACKGROUND: Atherosclerosis (AS) is the main cause of coronary heart disease, cerebral infarction, and peripheral vascular disease. QingRe HuoXue Formula (QRHXF), a common prescription of traditional Chinese medicine, has a definite effect on the clinical treatment of AS, but its mechanism remains to be further explored.

Predicting Intracranial Aneurysm Rupture: A Multifactor Analysis Combining Radscore, Morphology, and PHASES Parameters.

RATIONALE AND OBJECTIVES: We aimed at developing and validating a nomogram and machine learning (ML) models based on radiomics score (Radscore), morphology, and PHASES to predict intracranial aneurysm (IA) rupture.

Artificial Intelligence and Health Inequities in Dietary Interventions on Atherosclerosis: A Narrative Review.

Poor diet is the top modifiable mortality risk factor globally, accounting for 11 million deaths annually with half being from diet-linked atheroscler...

Derivation and external validation of mass spectrometry-based proteomic model using machine learning algorithms to predict plaque rupture in patients with acute coronary syndrome.

BACKGROUND: A poor prognosis is associated with atherosclerotic plaque rupture (PR) despite after conventional therapy for patients with acute coronar...

Deciphering breast cancer prognosis: a novel machine learning-driven model for vascular mimicry signature prediction.

BACKGROUND: In the ongoing battle against breast cancer, a leading cause of cancer-related mortality among women globally, the urgent need for innovat...

Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics data.

Integrating multi-omics data into predictive models has the potential to enhance accuracy, which is essential for precision medicine. In this study, w...

Development of machine learning models for fractional flow reserve prediction in angiographically intermediate coronary lesions.

BACKGROUND: Fractional flow reserve (FFR) represents the gold standard in guiding the decision to proceed or not with coronary revascularization of an...

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 i...

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, elev...

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...