Strokes

Efficacy and neural mechanisms of a vibrotactile-enhanced, brain-controlled soft robotic glove for upper limb rehabilitation after stroke: a multicentre randomised controlled trial protocol.

INTRODUCTION: Soft robotic gloves (SRGs) integrated with brain-computer interfaces (BCIs) have demon...

AI- vs Human-Based Assessment of Medical Interview Transcripts in a Generative AI-Simulated Patient System: Cross-Sectional Validation Study.

BACKGROUND: Generative artificial intelligence (AI) is increasingly used in medical education, inclu...

LeCoder: A large-scale automated coder for coding errors in word-production tasks.

Speech errors have been instrumental in advancing our understanding of the architecture of the langu...

Prediction of Major Stroke (NIHSS > 5) Based on MR Perfusion Imaging Using a 3D ResNet.

PURPOSE: Prediction of stroke symptoms from perfusion patterns in ischemic stroke imaging would be d...

​Aging-related gene signatures as potential biomarkers in ischemic stroke: an integrated bioinformatics and machine learning study.

Application of machine learning approaches to develop predictive models for diabetes and hypertension among Bangladeshi Adults.

With rapid urbanization, lifestyle changes, and an aging population, non-communicable diseases (NCDs...

Machine learning for dysphagia risk prediction in older adults after acute ischemic stroke.

Development and validation of an explainable machine learning prediction model for futile recanalization after mechanical thrombectomy in acute large vessel occlusion stroke.

BACKGROUND: Mechanical thrombectomy (MT) is the primary treatment for acute ischemic stroke (AIS) ca...

Proactive haemodynamic management using the hypotension prediction index during caesarean section: a randomised controlled study.

INTRODUCTION: Intra-operative hypotension is common during caesarean section and may result in adver...

Marine-Derived bioactive compounds from Aquaculture: Receptor-Mediated neuroprotection in neurodegenerative disorders.

Neurodegenerative diseases, like Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's di...

Machine Learning-Assisted Detection of Phosgene and Acetyl Chloride via a Dual-Probe Fluorescent Platform with Differential Reactivity.

Phosgene and acyl chlorides are highly toxic chemicals that pose serious threats to human health and...

The association between liver disease and stroke risk: A cross-sectional study with machine learning in a large-scale Chinese cohort.

INTRODUCTION: This study aimed to investigate the association between liver disease (LD) and stroke ...

Effect of Brain-Computer Interface-Controlled Ankle Robot Training on Post-Stroke Motor Rehabilitation and Resting QEEG Neuroplasticity: A Randomized Controlled Trial.

BACKGROUND: Persistent post-stroke ankle impairment hinders functional recovery. Brain-computer inte...

An integrative genomic framework to identify remote ischemic preconditioning-responsive genes associated with stroke risk.

BACKGROUND: Remote ischemic preconditioning (RIPC) is a promising, non-invasive strategy for reducti...

Deep Learning and Machine Learning for Differentiation Between Contrast Extravasation and Hemorrhagic Transformation in Post-Thrombectomy Stroke CT.

BACKGROUND: Mechanical thrombectomy (MT) improves outcomes in acute ischemic stroke (AIS) but often ...

Diagnosis of Cardiac Amyloidosis on Echocardiography Using Artificial Intelligence.

BACKGROUND: Diagnosing cardiac amyloidosis (CA) on echocardiography can be challenging due to the im...

Diagnostic model and identification of IGFBP2 as an aging-related biomarker and therapeutic target for systemic sclerosis-associated interstitial lung disease through integrated bioinformatics and machine learning approaches.

BACKGROUND: Cellular senescence is a critical contributor to the pathogenesis of systemic sclerosis-...

Explainable machine learning model based on clinical and radiological features for predicting hematoma expansion or rebleeding after decompressive craniectomy in traumatic brain injury: a bicentric cohort study.

BACKGROUND: Hematoma expansion or rebleeding after decompressive craniectomy (DC) is a critical dete...

A Strengths, Weaknesses, Opportunities, and Threats Analysis of Generative Artificial Intelligence in Aphasia Management With Proposed Ethical Guidelines.

PURPOSE: Generative artificial intelligence (GenAI) is rapidly emerging as a transformative technolo...

Leveraging natural language processing and machine learning to identify chronic conditions from primary care electronic medical records.

Primary care electronic medical records (EMRs) contain rich data that can support proactive identifi...

[Cardiology : what's new in 2025].

In 2025, significant progress has been made in the management of heart failure and cardiovascular di...