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Predicting Brain Amyloid Using Multivariate Morphometry Statistics, Sparse Coding, and Correntropy: Validation in 1,101 Individuals From the ADNI and OASIS Databases

Overview of attention for article published in Frontiers in Neuroscience, August 2021
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
6 X users

Readers on

mendeley
34 Mendeley
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Title
Predicting Brain Amyloid Using Multivariate Morphometry Statistics, Sparse Coding, and Correntropy: Validation in 1,101 Individuals From the ADNI and OASIS Databases
Published in
Frontiers in Neuroscience, August 2021
DOI 10.3389/fnins.2021.669595
Pubmed ID
Authors

Jianfeng Wu, Qunxi Dong, Jie Gui, Jie Zhang, Yi Su, Kewei Chen, Paul M. Thompson, Richard J. Caselli, Eric M. Reiman, Jieping Ye, Yalin Wang

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 15%
Other 3 9%
Student > Bachelor 3 9%
Student > Master 3 9%
Researcher 2 6%
Other 5 15%
Unknown 13 38%
Readers by discipline Count As %
Computer Science 6 18%
Medicine and Dentistry 4 12%
Neuroscience 3 9%
Engineering 2 6%
Physics and Astronomy 1 3%
Other 3 9%
Unknown 15 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 09 August 2021.
All research outputs
#7,778,513
of 25,547,904 outputs
Outputs from Frontiers in Neuroscience
#4,917
of 11,609 outputs
Outputs of similar age
#149,259
of 438,714 outputs
Outputs of similar age from Frontiers in Neuroscience
#134
of 401 outputs
Altmetric has tracked 25,547,904 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 11,609 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has gotten more attention than average, scoring higher than 57% 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 438,714 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 401 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.