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Multimodal MRI-Based Triage for Acute Stroke Therapy: Challenges and Progress

Overview of attention for article published in Frontiers in Neurology, July 2018
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Title
Multimodal MRI-Based Triage for Acute Stroke Therapy: Challenges and Progress
Published in
Frontiers in Neurology, July 2018
DOI 10.3389/fneur.2018.00586
Pubmed ID
Authors

Oh Young Bang, Jong-Won Chung, Jeong Pyo Son, Wi-Sun Ryu, Dong-Eog Kim, Woo-Keun Seo, Gyeong-Moon Kim, Yoon-Chul Kim

Abstract

Revascularization therapies have been established as the treatment mainstay for acute ischemic stroke. However, a substantial number of patients are either ineligible for revascularization therapy, or the treatment fails or is futile. At present, non-contrast computed tomography is the first-line neuroimaging modality for patients with acute stroke. The use of magnetic resonance imaging (MRI) to predict the response to early revascularization therapy and to identify patients for delayed treatment is desirable. MRI could provide information on stroke pathophysiologies, including the ischemic core, perfusion, collaterals, clot, and blood-brain barrier status. During the past 20 years, there have been significant advances in neuroimaging as well as in revascularization strategies for treating patients with acute ischemic stroke. In this review, we discuss the role of MRI and post-processing, including machine-learning techniques, and recent advances in MRI-based triage for revascularization therapies in acute ischemic stroke.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 60 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 8 13%
Student > Ph. D. Student 7 12%
Researcher 5 8%
Student > Master 5 8%
Student > Doctoral Student 4 7%
Other 12 20%
Unknown 19 32%
Readers by discipline Count As %
Medicine and Dentistry 10 17%
Computer Science 5 8%
Neuroscience 5 8%
Engineering 4 7%
Nursing and Health Professions 3 5%
Other 8 13%
Unknown 25 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 July 2018.
All research outputs
#20,527,576
of 23,096,849 outputs
Outputs from Frontiers in Neurology
#9,028
of 12,015 outputs
Outputs of similar age
#288,196
of 329,806 outputs
Outputs of similar age from Frontiers in Neurology
#240
of 310 outputs
Altmetric has tracked 23,096,849 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,015 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 310 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.