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Support Vector Machine for Analyzing Contributions of Brain Regions During Task-State fMRI

Overview of attention for article published in Frontiers in Neuroinformatics, March 2019
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57 Mendeley
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Title
Support Vector Machine for Analyzing Contributions of Brain Regions During Task-State fMRI
Published in
Frontiers in Neuroinformatics, March 2019
DOI 10.3389/fninf.2019.00010
Pubmed ID
Authors

Mengyue Wang, Chunlin Li, Wenjing Zhang, Yonghao Wang, Yuan Feng, Ying Liang, Jing Wei, Xu Zhang, Xia Li, Renji Chen

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 21%
Student > Ph. D. Student 9 16%
Student > Bachelor 4 7%
Student > Postgraduate 3 5%
Lecturer 3 5%
Other 2 4%
Unknown 24 42%
Readers by discipline Count As %
Neuroscience 11 19%
Psychology 4 7%
Computer Science 4 7%
Biochemistry, Genetics and Molecular Biology 3 5%
Engineering 3 5%
Other 7 12%
Unknown 25 44%
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 19 March 2019.
All research outputs
#19,789,791
of 24,319,828 outputs
Outputs from Frontiers in Neuroinformatics
#665
of 798 outputs
Outputs of similar age
#272,800
of 356,799 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#16
of 21 outputs
Altmetric has tracked 24,319,828 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 798 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 9th percentile – i.e., 9% 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 356,799 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.