Strokes

Pre-interventional transesophageal echocardiography as a reliable predictor of residual shunt following patent foramen ovale closure.

BACKGROUND: Closure of a patent foramen ovale (PFO) is an effective strategy in the prevention of re...

Comparison of the effects of robot-assisted gait training using FES versus virtual reality for stroke patients. A randomized clinical trial.

BACKGROUND: Robot-assisted gait training is becoming an effective alternative to therapist-assisted ...

Assessment and management of portal hypertension in patients with MASLD: advances and caveats.

INTRODUCTION: Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly gaini...

Inflammatory, fibrotic and endothelial biomarker profiles in COVID-19 patients during and following hospitalization.

Survivors of severe COVID-19 often suffer from long-term respiratory issues, but the molecular drive...

A machine learning model reveals invisible microscopic variation in acute ischaemic stroke (≤ 6 h) with non-contrast computed tomography.

BACKGROUND: In most medical centers, particularly in primary hospitals, non-contrast computed tomogr...

Evolution of CT perfusion software in stroke imaging: from deconvolution to artificial intelligence.

Computed tomography perfusion (CTP) represents one of the main determinants in the decision-making s...

Unsupervised learning using EHR and census data to identify distinct subphenotypes of newly diagnosed hypertension patients.

BACKGROUND: Hypertension (HTN) is a complex condition with significant heterogeneity in presentation...

Enhancing stroke risk prediction through class balancing and data augmentation with CBDA-ResNet50.

Accurate prediction of stroke risk at an early stage is essential for timely intervention and preven...

Integrating Machine Learning into Myositis Research: a Systematic Review.

Idiopathic inflammatory myopathies (IIM) are a group of autoimmune rheumatic diseases characterized ...

Artificial intelligence and digital twins for the personalised prediction of hypertension risk.

Hypertension is a significant global health challenge, contributing substantially to morbidity and m...

Feature selection using metaheuristics to predict annual amyotrophic lateral sclerosis progression.

OBJECTIVE: Amyotrophic lateral sclerosis (ALS), a progressive neurodegenerative disease with no cura...

Deep Learning based Collateral Scoring on Multi-Phase CTA in patients with acute ischemic stroke in MCA region.

BACKGROUND AND PURPOSE: Collateral circulation is a critical determinant of clinical outcomes in acu...

Correction to "Deep Learning Enhanced Near Infrared-II Imaging and Image-Guided Small Interfering Ribonucleic Acid Therapy of Ischemic Stroke".

An enhanced fusion of transfer learning models with optimization based clinical diagnosis of lung and colon cancer using biomedical imaging.

Lung and colon cancers (LCC) are among the foremost reasons for human death and disease. Early analy...

Effects of device-assisted practice of activities of daily living in a close-to-normal pattern on upper extremity motor recovery in individuals with moderate to severe stroke: study protocol of a randomized control trial.

BACKGROUND: The majority of individuals with chronic stroke have residual upper extremity (UE) disab...

Exploratory development of human-machine interaction strategies for post-stroke upper-limb rehabilitation.

BACKGROUND: Stroke and its related complications, place significant burdens on human society in the ...

Machine learning-based prognostic prediction for acute ischemic stroke using whole-brain and infarct multi-PLD ASL radiomics.

INTRODUCTION: Accurate early prognostic prediction for acute ischemic stroke (AIS) is essential for ...

Network-based machine learning reveals cardiometabolic multimorbidity patterns and modifiable lifestyle factors: a community-focused analysis of NHANES 2015-2018.

Cardiometabolic Multimorbidity (CMM) has emerged as one of the primary threats to human health globa...

Beyond Recanalization: Machine Learning-Based Insights into Post-Thrombectomy Vascular Morphology in Stroke Patients.

Many stroke patients have poor outcomes despite successful endovascular therapy (EVT). We hypothesiz...

Artificial Intelligence-Enhanced Electrocardiography for Prediction of Occult Atrial Fibrillation in Patients With Stroke Who Undergo Prolonged Cardiac Monitoring.

OBJECTIVE: To evaluate the performance of an artificial intelligence (AI)-enhanced electrocardiograp...

Identifying predictors and assessing causal effect on hypertension risk among adults using Double Machine Learning models: Insights from Bangladesh Demographic and Health Survey.

BACKGROUND: Hypertension poses a significant public health challenge in low- and middle-income count...