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A novel deep learning approach for diagnosing Alzheimer's disease based on eye-tracking data

Overview of attention for article published in Frontiers in Human Neuroscience, September 2022
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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 (84th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

news
1 news outlet
twitter
2 X users

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
36 Mendeley
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Title
A novel deep learning approach for diagnosing Alzheimer's disease based on eye-tracking data
Published in
Frontiers in Human Neuroscience, September 2022
DOI 10.3389/fnhum.2022.972773
Pubmed ID
Authors

Jinglin Sun, Yu Liu, Hao Wu, Peiguang Jing, Yong Ji

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

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 11%
Student > Ph. D. Student 3 8%
Professor 2 6%
Unspecified 2 6%
Student > Doctoral Student 1 3%
Other 3 8%
Unknown 21 58%
Readers by discipline Count As %
Computer Science 4 11%
Unspecified 2 6%
Medicine and Dentistry 2 6%
Neuroscience 2 6%
Linguistics 1 3%
Other 4 11%
Unknown 21 58%
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 30 September 2022.
All research outputs
#3,233,303
of 23,443,716 outputs
Outputs from Frontiers in Human Neuroscience
#1,595
of 7,294 outputs
Outputs of similar age
#66,866
of 433,461 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#17
of 177 outputs
Altmetric has tracked 23,443,716 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,294 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one has done well, scoring higher than 78% 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 433,461 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 84% of its contemporaries.
We're also able to compare this research output to 177 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.