AIMC Topic: Ischemic Stroke

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Assessing electrocardiogram changes after ischemic stroke with artificial intelligence.

PloS one
OBJECTIVE: Ischemic stroke (IS) with subsequent cerebrocardiac syndrome (CCS) has a poor prognosis. We aimed to investigate electrocardiogram (ECG) changes after IS with artificial intelligence (AI).

Automated estimation of ischemic core volume on noncontrast-enhanced CT via machine learning.

Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
BACKGROUND: Accurate estimation of ischemic core on baseline imaging has treatment implications in patients with acute ischemic stroke (AIS). Machine learning (ML) algorithms have shown promising results in estimating ischemic core using routine nonc...

Predicting Hypoperfusion Lesion and Target Mismatch in Stroke from Diffusion-weighted MRI Using Deep Learning.

Radiology
Background Perfusion imaging is important to identify a target mismatch in stroke but requires contrast agents and postprocessing software. Purpose To use a deep learning model to predict the hypoperfusion lesion in stroke and identify patients with ...

Artificial intelligence for localization of the acute ischemic stroke by non-contrast computed tomography.

PloS one
A non-contrast cranial computer tomography (ncCT) is often employed for the diagnosis of the early stage of the ischemic stroke. However, the number of false negatives is high. More accurate results are obtained by an MRI. However, the MRI is not ava...

Deep learning prediction of stroke thrombus red blood cell content from multiparametric MRI.

Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
BACKGROUND AND PURPOSE: Thrombus red blood cell (RBC) content has been shown to be a significant factor influencing the efficacy of acute ischemic stroke treatment. In this study, our objective was to evaluate the ability of convolutional neural netw...

Word2vec Word Embedding-Based Artificial Intelligence Model in the Triage of Patients with Suspected Diagnosis of Major Ischemic Stroke: A Feasibility Study.

International journal of environmental research and public health
BACKGROUND: The possible benefits of using semantic language models in the early diagnosis of major ischemic stroke (MIS) based on artificial intelligence (AI) are still underestimated. The present study strives to assay the feasibility of the word2v...

Deep Learning in Ischemic Stroke Imaging Analysis: A Comprehensive Review.

BioMed research international
Ischemic stroke is a cerebrovascular disease with a high morbidity and mortality rate, which poses a serious challenge to human health and life. Meanwhile, the management of ischemic stroke remains highly dependent on manual visual analysis of noncon...

Automatic identification of early ischemic lesions on non-contrast CT with deep learning approach.

Scientific reports
Early ischemic lesion on non-contrast computed tomogram (NCCT) in acute stroke can be subtle and need confirmation with magnetic resonance (MR) image for treatment decision-making. We retrospectively included the NCCT slices of 129 normal subjects an...

Identifying acute ischemic stroke patients within the thrombolytic treatment window using deep learning.

Journal of neuroimaging : official journal of the American Society of Neuroimaging
BACKGROUND AND PURPOSE: Treatment of acute ischemic stroke is heavily contingent upon time, as there is a strong relationship between time clock and tissue progression. Work has established imaging biomarker assessments as surrogates for time since s...

Adaptive wireless millirobotic locomotion into distal vasculature.

Nature communications
Microcatheters have enabled diverse minimally invasive endovascular operations and notable health benefits compared with open surgeries. However, with tortuous routes far from the arterial puncture site, the distal vascular regions remain challenging...