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A Novel Unit-Based Personalized Fingerprint Feature Selection Strategy for Dynamic Functional Connectivity Networks

Overview of attention for article published in Frontiers in Neuroscience, March 2021
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Mentioned by

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3 X users

Citations

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5 Dimensions

Readers on

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6 Mendeley
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Title
A Novel Unit-Based Personalized Fingerprint Feature Selection Strategy for Dynamic Functional Connectivity Networks
Published in
Frontiers in Neuroscience, March 2021
DOI 10.3389/fnins.2021.651574
Pubmed ID
Authors

Feng Zhao, Zhiyuan Chen, Islem Rekik, Peiqiang Liu, Ning Mao, Seong-Whan Lee, Dinggang Shen

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users 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 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 50%
Student > Master 1 17%
Unknown 2 33%
Readers by discipline Count As %
Chemical Engineering 1 17%
Psychology 1 17%
Neuroscience 1 17%
Engineering 1 17%
Unknown 2 33%
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 08 April 2021.
All research outputs
#17,297,846
of 25,387,668 outputs
Outputs from Frontiers in Neuroscience
#8,086
of 11,543 outputs
Outputs of similar age
#283,880
of 452,551 outputs
Outputs of similar age from Frontiers in Neuroscience
#319
of 403 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,543 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 24th percentile – i.e., 24% 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 452,551 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 403 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.