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Machine Learning Based Classification of Resting-State fMRI Features Exemplified by Metabolic State (Hunger/Satiety)

Overview of attention for article published in Frontiers in Human Neuroscience, May 2019
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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5 X users

Citations

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32 Dimensions

Readers on

mendeley
102 Mendeley
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Title
Machine Learning Based Classification of Resting-State fMRI Features Exemplified by Metabolic State (Hunger/Satiety)
Published in
Frontiers in Human Neuroscience, May 2019
DOI 10.3389/fnhum.2019.00164
Pubmed ID
Authors

Arkan Al-Zubaidi, Alfred Mertins, Marcus Heldmann, Kamila Jauch-Chara, Thomas F. Münte

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 102 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 22%
Researcher 18 18%
Student > Bachelor 12 12%
Student > Master 12 12%
Student > Doctoral Student 7 7%
Other 10 10%
Unknown 21 21%
Readers by discipline Count As %
Neuroscience 19 19%
Computer Science 15 15%
Engineering 12 12%
Psychology 10 10%
Medicine and Dentistry 7 7%
Other 10 10%
Unknown 29 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 28 March 2020.
All research outputs
#13,826,741
of 24,652,007 outputs
Outputs from Frontiers in Human Neuroscience
#3,570
of 7,526 outputs
Outputs of similar age
#162,562
of 355,304 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#51
of 100 outputs
Altmetric has tracked 24,652,007 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,526 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.9. This one has gotten more attention than average, scoring higher than 51% 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 355,304 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 53% of its contemporaries.
We're also able to compare this research output to 100 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.