Strokes

Machine learning-based prediction of fall within 6 months of stroke onset: A prospective study.

OBJECTIVE: To develop and evaluate machine learning-based models for predicting fall risk within 6 months of stroke onset. METHODS: This prospective study enrolled acute stroke patients from three tertiary hospitals in Gansu Province, China. The study was conducted from December 2022 to October 2024. Participants were followed for 6 months. Two machine learning algorithms, decision tree (DT) and l...

Recent advances and knowledge gaps in anticoagulation strategy with durable left ventricular assist devices.

Driven by technological advancements, donor shortages, and an aging population, utilization of left ventricular assist devices (LVAD), both as a bridge to transplant and as destination therapy, has risen in recent years for symptomatic patients with end-stage heart failure. With wide blood flow pathways, friction-free movement, and intrinsic pulsatility that reduce shear stress and promote more fa...

Transient Ischemic Attack Diagnosis using Explicit Criteria Outperforms Artificial Intelligence: a Prospective Cohort Study.

BACKGROUND: Diagnosing transient ischemic attacks (TIAs) remains challenging, particularly in primary care and emergency department settings where spe...

Clinical significance of lncRNA-miRNA axes in ischemic stroke: Diagnostic value, prognostic relevance, and therapeutic potential.

Ischemic stroke and subsequent reperfusion injury are major causes of mortality and long-term neurological disability, driven by complex mechanisms of...

An Interpretable Machine Learning Framework with Clinical Nomogram for Predicting In-Hospital Mortality in Acute Ischemic Stroke Using High-Granularity Bedside Data.

BACKGROUND: This multicenter study developed and validated an interpretable machine learning model integrating granular nursing and emergency departme...

tDCS synchronous robotic training on lower-limb with post-stroke hemiplegia: a comparative study between synchronous and sequential group.

BACKGROUND: This study was aimed to compare the effects of tDCS synchronized with robotic training(RT)and tDCS sequential followed by RT on lower-limb...

Bioinformatics and Machine-Learning Identification of Pulmonary Hypertension Biomarkers and Candidate Therapeutic Compounds.

This study aimed to identify pulmonary hypertension (PH)-associated molecular biomarkers and candidate small-molecule compounds using public transcrip...

[Personalized lower-limb gait assessment method based on musculoskeletal modeling and machine learning].

To address the issues of insufficient objectivity and difficulty in locating muscle dysfunction in current lower-limb gait assessment methods, this pa...

The Imaging Compass: Navigating Reperfusion in Acute Ischemic Stroke.

The management of acute ischemic stroke has shifted from rigid time-based protocols to imaging-driven, tissue-based reperfusion strategies. Non-contra...

Reducing Racial Disparities in Stroke Thrombolysis Using Fairness-Aware Machine Learning.

Racial and ethnic disparities in the administration of intravenous thrombolysis (IVT) for acute ischemic stroke (AIS) remain persistent, raising conce...

Left ventricular hypertrophy as a predictor of adverse maternal and neonatal outcomes in chronic hypertension in pregnancy: a multicenter study.

OBJECTIVE: The impact of chronic hypertension (CHTN) combined with left ventricular hypertrophy (LVH) on adverse maternal and fetal pregnancy outcomes...

Glycolysis, Inflammation, and Mitochondrial Dysfunction: New Perspectives on the Pathogenesis of Hypertension.

BACKGROUND: Recent studies show enhanced glycolysis is linked to chronic diseases, but its relationship with hypertension is unclear. This study explo...

Small Intracerebral Hemorrhage: Baseline CT Edema-to-Hematoma Ratio as an Independent Predictor of Early Expansion.

BACKGROUND AND PURPOSE: Small intracerebral hemorrhage (ICH), defined as baseline NCCT hematoma volume (HV) <30 mL, is often considered lower risk for...

A ciliated intravascular soft millirobot for multimodal in-flow collective manipulation.

The laminar nature of blood flow and the resulting boundary layer pose substantial challenges for transverse mass transport in blood vessels, limiting...

Mechanisms of brain-body interactions in post-stroke visceral dysfunction and recovery.

Traditionally, stroke has been characterized as an acute focal brain injury; however, its clinical consequences extend beyond neurological deficits to...

Computed Tomographic Angiography-Based Radiomics Predicted Stroke Recurrence in Patients With Symptomatic Intracranial Atherosclerotic Stenosis.

BACKGROUND: The aim of the current study was to investigate the predictive values of computed tomographic angiography-derived radiomics features (RFs)...

Systematic Review on Noncomputed Tomography-Based Technologies for Prehospital Stroke Diagnosis.

Effects of stroke therapies area highly time dependent but onset-to-treatment times for recanalizing treatment are mostly beyond optimal time windows....

Prediction of Atrial Fibrillation Occurrence With Handheld Mobile Electrocardiogram: Deep Learning Model Development Using Real-World Data.

BACKGROUND: Atrial fibrillation (AF) is a common arrhythmia associated with an increased risk of stroke and heart failure. To improve prevention, rece...

Decision-making logic for samples of clinically significant EDTA-dependent pseudothrombocytopenia with machine learning.

OBJECTIVES: To establish practical, clinically meaningful criteria for identifying significant platelet aggregation in suspected samples, defined by a...

SCRIB is a Shared Transcriptomic Biomarker Candidate Linking Cardioembolic Stroke and Alzheimer's Disease.

Acute ischemic stroke is a major cause of death and disability, and post-stroke cognitive impairment remains a major clinical challenge. Cardioembolic...