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Topological Properties of Resting-State fMRI Functional Networks Improve Machine Learning-Based Autism Classification

Overview of attention for article published in Frontiers in Neuroscience, January 2019
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2 X users

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138 Mendeley
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Title
Topological Properties of Resting-State fMRI Functional Networks Improve Machine Learning-Based Autism Classification
Published in
Frontiers in Neuroscience, January 2019
DOI 10.3389/fnins.2018.01018
Pubmed ID
Authors

Amirali Kazeminejad, Roberto C. Sotero

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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 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 138 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 18%
Student > Master 21 15%
Student > Bachelor 14 10%
Researcher 9 7%
Student > Doctoral Student 5 4%
Other 14 10%
Unknown 50 36%
Readers by discipline Count As %
Computer Science 19 14%
Neuroscience 16 12%
Engineering 15 11%
Psychology 10 7%
Medicine and Dentistry 8 6%
Other 14 10%
Unknown 56 41%
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 29 January 2019.
All research outputs
#20,663,600
of 25,385,509 outputs
Outputs from Frontiers in Neuroscience
#9,473
of 11,543 outputs
Outputs of similar age
#340,595
of 446,242 outputs
Outputs of similar age from Frontiers in Neuroscience
#253
of 306 outputs
Altmetric has tracked 25,385,509 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 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 11th percentile – i.e., 11% 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 446,242 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 306 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.