Artificial intelligence technology is a rapidly expanding field with many applications in acute
stroke imaging, including ischemic and hemorrhage subtypes. Early identification of acute …

Management of stroke highly depends on informa-tion from imaging studies. Noncontrast
computed tomography (CT) and magnetic resonance imaging (MRI) can both be used to …

Background and objective In recent years, deep learning algorithms have created a massive
impact on addressing research challenges in different domains. The medical field also …

Stroke remains one of the leading causes of death and disability in Europe. The European
Stroke Action Plan (ESAP) defines four main targets for the years 2018 to 2030. The COVID …

Background: Established randomized trial-based parameters for acute ischemic stroke
group patients into generic treatment groups, leading to attempts using various artificial …

Deep Learning (DL) algorithm holds great potential in the field of stroke imaging. It has been
applied not only to the “downstream” side such as lesion detection, treatment decision …

Machine learning (ML) has been proposed for lesion segmentation in acute ischemic stroke
(AIS). This study aimed to provide a systematic review and meta-analysis of the overall …

Ischemic stroke is a serious disease posing significant threats to human health and life, with
the highest absolute and relative risks of a poor prognosis following the first occurrence, and …

Fueled by new techniques, computational tools, and broader availability of imaging data,
artificial intelligence has the potential to transform the practice of neuroradiology. The recent …

Deep learning (DL) is a powerful machine learning technique that has increasingly been
used to predict surgical outcomes. However, the large quantity of data required and lack of …