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Differentiating Boys with ADHD from Those with Typical Development Based on Whole-Brain Functional Connections Using a Machine Learning Approach

Overview of attention for article published in Neuropsychiatric Disease and Treatment, March 2020
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About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 X user
facebook
2 Facebook pages

Citations

dimensions_citation
23 Dimensions

Readers on

mendeley
54 Mendeley
Title
Differentiating Boys with ADHD from Those with Typical Development Based on Whole-Brain Functional Connections Using a Machine Learning Approach
Published in
Neuropsychiatric Disease and Treatment, March 2020
DOI 10.2147/ndt.s239013
Pubmed ID
Authors

Yunkai Sun, Lei Zhao, Zhihui Lan, Xi-Ze Jia, Shao-Wei Xue

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

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 15%
Student > Bachelor 6 11%
Student > Ph. D. Student 5 9%
Student > Doctoral Student 3 6%
Unspecified 3 6%
Other 8 15%
Unknown 21 39%
Readers by discipline Count As %
Neuroscience 8 15%
Psychology 7 13%
Medicine and Dentistry 5 9%
Engineering 3 6%
Unspecified 3 6%
Other 6 11%
Unknown 22 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 10 March 2020.
All research outputs
#17,295,853
of 25,387,668 outputs
Outputs from Neuropsychiatric Disease and Treatment
#1,902
of 3,131 outputs
Outputs of similar age
#243,820
of 383,477 outputs
Outputs of similar age from Neuropsychiatric Disease and Treatment
#32
of 61 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 3,131 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 30th percentile – i.e., 30% 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 383,477 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.