Latest AI and machine learning research in strokes for healthcare professionals.
BACKGROUND AND OBJECTIVE: Atrial fibrillation (AF) is a significant cause of life-threatening heart ...
The Arteriovenous Access Stage (AVAS) classification simplifies information about suitability of ves...
BackgroundIntensive care unit (ICU) acquired weakness is a detrimental condition characterized by mu...
Pompe disease is a neuromuscular disorder caused by a deficiency of the enzyme acid alpha-glucosidas...
To validate the clinical feasibility of deep learning-driven magnetic resonance angiography (DL-driv...
INTRODUCTION: Hypertension is a significant public health concern. Several relevant risk factors hav...
Intracranial atherosclerotic stenosis (ICAS) and intracranial aneurysms are prevalent conditions in ...
BACKGROUND: Hemorrhagic transformation (HT) is a complication of reperfusion therapy following acute...
OBJECTIVE: To develop and validate an explainable machine learning (ML) model predicting the risk of...
INTRODUCTION: The growing demand for real-time, affordable, and accessible healthcare has underscore...
BACKGROUND: Programmed cell death plays an important role in neuronal injury and death after ischemi...
INTRODUCTION: Early prognosis prediction of acute ischemic stroke (AIS) can support clinicians in ch...
BACKGROUND: Spontaneous intracerebral hemorrhage (SICH) is the second most common cause of cerebrova...
BackgroundIschemic stroke is a critical neurological condition, with infection representing a signif...
INTRODUCTION: Delirium, frequently experienced by ischemic stroke patients, is one of the most commo...
BACKGROUND: Dabigatran etexilate (DABE), a prodrug of dabigatran (DAB), is a direct thrombin inhibit...
OBJECTIVES: Sufficient attention has not been given to machine learning (ML) models using longitudin...
BACKGROUND AND PURPOSE: DWI is crucial for detecting infarction stroke. However, its spatial resolut...
Pulmonary hypertension (PH) is a complex condition associated with significant morbidity and mortal...
Detecting early ischemic lesions (EIL) in computed tomography (CT) images is crucial for reducing di...
OBJECTIVE: To develop a machine learning-based model for predicting the clinical efficacy of acupunc...