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Early Identification of High-Risk TIA or Minor Stroke Using Artificial Neural Network

Overview of attention for article published in Frontiers in Neurology, March 2019
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1 X user

Citations

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35 Dimensions

Readers on

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44 Mendeley
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Title
Early Identification of High-Risk TIA or Minor Stroke Using Artificial Neural Network
Published in
Frontiers in Neurology, March 2019
DOI 10.3389/fneur.2019.00171
Pubmed ID
Authors

Ka Lung Chan, Xinyi Leng, Wei Zhang, Weinan Dong, Quanli Qiu, Jie Yang, Yannie Soo, Ka Sing Wong, Thomas W. Leung, Jia Liu

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 14%
Researcher 4 9%
Student > Ph. D. Student 4 9%
Student > Doctoral Student 4 9%
Student > Bachelor 4 9%
Other 12 27%
Unknown 10 23%
Readers by discipline Count As %
Medicine and Dentistry 10 23%
Computer Science 9 20%
Neuroscience 3 7%
Sports and Recreations 2 5%
Engineering 2 5%
Other 8 18%
Unknown 10 23%
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 06 March 2019.
All research outputs
#20,557,521
of 23,132,033 outputs
Outputs from Frontiers in Neurology
#9,042
of 12,042 outputs
Outputs of similar age
#304,988
of 354,050 outputs
Outputs of similar age from Frontiers in Neurology
#266
of 382 outputs
Altmetric has tracked 23,132,033 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 12,042 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.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 354,050 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 382 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.