Strokes

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...

Development and Validation of a Nomogram for Predicting Oral Frailty Risk in Elderly Patients With Ischaemic Stroke.

AIM: To develop and validate a risk prediction model for oral frailty in elderly patients with ischa...

Integrating Machine Learning into Myositis Research: a Systematic Review.

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

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

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...

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...

Cost-effectiveness analysis of robotic exoskeleton versus conventional physiotherapy for stroke rehabilitation in Singapore from a health system perspective.

OBJECTIVES: This study conducted a comprehensive probabilistic cost-effectiveness analysis comparing...

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...

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

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

Neuroimaging and biological markers of different paretic hand outcomes after stroke.

BACKGROUND: Hand dysfunction significantly affects independence after stroke, with outcomes varying ...

Research on transcranial magnetic stimulation for stroke rehabilitation: a visual analysis based on CiteSpace.

OBJECTIVE: This study aimed to analyze recent research and emerging trends in transcranial magnetic ...

AI-ECG for early detection of atrial fibrillation: First-year results from a stroke prevention study in Shimizu, Japan.

BACKGROUND: An artificial intelligence algorithm-guided electrocardiogram (AI-ECG) has been develope...

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...

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 ...

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 ...

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...