Strokes

Exploring new horizons: Emerging therapeutic strategies for pediatric stroke.

Pediatric stroke presents unique challenges, and optimizing treatment strategies is essential for improving outcomes in this vulnerable population. This review aims to provide an overview of new, innovative, and potential treatments for pediatric stroke, with a primary objective to stimulate further research in this field. Our review highlights several promising approaches in the realm of pediatri...

Artificial intelligence-based decision support software to improve the efficacy of acute stroke pathway in the NHS: an observational study.

INTRODUCTION: In a drip-and-ship model for endovascular thrombectomy (EVT), early identification of large vessel occlusion (LVO) and timely referral to a comprehensive center (CSC) are crucial when patients are admitted to an acute stroke center (ASC). Several artificial intelligence (AI) decision-aid tools are increasingly being used to facilitate the rapid identification of LVO. This retrospecti...

A Machine Learning Approach to Predict Post-stroke Fatigue. The Nor-COAST study.

OBJECTIVE: This study aimed to predict fatigue 18 months post-stroke by utilizing comprehensive data from the acute and sub-acute phases after stroke ...

Transferring a deep learning model from healthy subjects to stroke patients in a motor imagery brain-computer interface.

Motor imagery (MI) brain-computer interfaces (BCIs) based on electroencephalogram (EEG) have been developed primarily for stroke rehabilitation, howev...

Rehabilitation Evaluation of Upper Limb Motor Function for Stroke Patients Based on Belief Rule Base.

In the process of rehabilitation treatment for stroke patients, rehabilitation evaluation is a significant part in rehabilitation medicine. Researcher...

Recent developments in machine learning modeling methods for hypertension treatment.

Hypertension is the leading cause of cardiovascular complications. This review focuses on the advancements in medical artificial intelligence (AI) mod...

Uncovering the Neural Mechanisms of Inter-Hemispheric Balance Restoration in Chronic Stroke Through EMG-Driven Robot Hand Training: Insights From Dynamic Causal Modeling.

EMG-driven robot hand training can facilitate motor recovery in chronic stroke patients by restoring the interhemispheric balance between motor networ...

Using Artificial Intelligence to Predict Intracranial Hypertension in Patients After Traumatic Brain Injury: A Systematic Review.

Intracranial hypertension (IH) is a key driver of secondary brain injury in patients with traumatic brain injury. Lowering intracranial pressure (ICP)...

Identification and validation of platelet-related diagnostic markers and potential drug screening in ischemic stroke by integrating comprehensive bioinformatics analysis and machine learning.

BACKGROUND: Ischemic stroke (IS), caused by blood and oxygen deprivation due to cerebral thrombosis, has links to activated and aggregated platelets. ...

Association between plain water intake and risk of hypertension: longitudinal analyses from the China Health and Nutrition Survey.

OBJECTIVE: This study aimed to investigate the prospective association between plain water intake and the risk of hypertension based on a longitudinal...

An interpretable machine learning model for stroke recurrence in patients with symptomatic intracranial atherosclerotic arterial stenosis.

BACKGROUND AND OBJECTIVE: Symptomatic intracranial atherosclerotic stenosis (SICAS) is the most common etiology of ischemic stroke and one of the main...

The Artificial Intelligence Revolution in Stroke Care: A Decade of Scientific Evidence in Review.

BACKGROUND: The emergence of artificial intelligence (AI) has significantly influenced the diagnostic evaluation of stroke and has revolutionized acut...

Factors affecting the efficiency of walking independence in patients with subacute stroke following robot-assisted gait training with conventional rehabilitation.

Factors affecting the efficiency of walking independence in patients with subacute stroke following robot-assisted gait training (RAGT) and convention...

Application of eHealth Tools in Anticoagulation Management After Cardiac Valve Replacement: Scoping Review Coupled With Bibliometric Analysis.

BACKGROUND: Anticoagulation management can effectively prevent complications in patients undergoing cardiac valve replacement (CVR). The emergence of ...

Effects of an assist-as-needed equipped Tenodesis-Induced-Grip Exoskeleton Robot (TIGER) on upper limb function in patients with chronic stroke.

BACKGROUND: The original version of the Tenodesis-Induced-Grip Exoskeleton Robot (TIGER) significantly improved the motor and functional performance o...

Prediction of stroke patients' bedroom-stay duration: machine-learning approach using wearable sensor data.

The importance of being physically active and avoiding staying in bed has been recognized in stroke rehabilitation. However, studies have pointed out...

Response to Letter Regarding the Article "Automated Segmentation of Intracranial Thrombus on NCCT and CTA in Patients with Acute Ischemic Stroke Using a Coarse-to-Fine Deep Learning Model".

Investigating Activity Recognition for Hemiparetic Stroke Patients Using Wearable Sensors: A Deep Learning Approach with Data Augmentation.

Measuring the daily use of an affected limb after hospital discharge is crucial for hemiparetic stroke rehabilitation. Classifying movements using non...

Multi-Objective Optimization of a Long-Stroke Moving-Iron Proportional Solenoid Actuator.

In this study, the performance of a long-stroke moving-iron proportional solenoid actuator (MPSA) was improved by combining numerical simulations and ...

Using Generative Artificial Intelligence to Classify Primary Progressive Aphasia from Connected Speech.

Neurodegenerative dementia syndromes, such as Primary Progressive Aphasias (PPA), have traditionally been diagnosed based in part on verbal and nonver...