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Using Multivariate Machine Learning Methods and Structural MRI to Classify Childhood Onset Schizophrenia and Healthy Controls

Overview of attention for article published in Frontiers in Psychiatry, January 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

twitter
17 X users

Citations

dimensions_citation
68 Dimensions

Readers on

mendeley
121 Mendeley
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Title
Using Multivariate Machine Learning Methods and Structural MRI to Classify Childhood Onset Schizophrenia and Healthy Controls
Published in
Frontiers in Psychiatry, January 2012
DOI 10.3389/fpsyt.2012.00053
Pubmed ID
Authors

Deanna Greenstein, James D. Malley, Brian Weisinger, Liv Clasen, Nitin Gogtay

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 17 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 121 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Unknown 119 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 19%
Researcher 22 18%
Student > Master 18 15%
Student > Bachelor 13 11%
Student > Postgraduate 7 6%
Other 17 14%
Unknown 21 17%
Readers by discipline Count As %
Neuroscience 21 17%
Psychology 19 16%
Engineering 17 14%
Medicine and Dentistry 11 9%
Computer Science 9 7%
Other 15 12%
Unknown 29 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 21 October 2017.
All research outputs
#3,765,613
of 26,567,854 outputs
Outputs from Frontiers in Psychiatry
#2,261
of 13,237 outputs
Outputs of similar age
#28,090
of 254,852 outputs
Outputs of similar age from Frontiers in Psychiatry
#19
of 86 outputs
Altmetric has tracked 26,567,854 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,237 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.7. This one has done well, scoring higher than 82% of its peers.
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 254,852 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 86 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.