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Prediction of conversion to dementia using interpretable machine learning in patients with amnestic mild cognitive impairment

Overview of attention for article published in Frontiers in Aging Neuroscience, August 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 (83rd percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

news
1 news outlet
twitter
1 X user

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
46 Mendeley
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Title
Prediction of conversion to dementia using interpretable machine learning in patients with amnestic mild cognitive impairment
Published in
Frontiers in Aging Neuroscience, August 2022
DOI 10.3389/fnagi.2022.898940
Pubmed ID
Authors

Min Young Chun, Chae Jung Park, Jonghyuk Kim, Jee Hyang Jeong, Hyemin Jang, Kyunga Kim, Sang Won Seo

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

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 7%
Student > Bachelor 3 7%
Unspecified 2 4%
Lecturer 2 4%
Professor 2 4%
Other 6 13%
Unknown 28 61%
Readers by discipline Count As %
Medicine and Dentistry 7 15%
Psychology 4 9%
Unspecified 2 4%
Engineering 2 4%
Chemical Engineering 1 2%
Other 3 7%
Unknown 27 59%
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 26 August 2022.
All research outputs
#3,223,947
of 24,334,327 outputs
Outputs from Frontiers in Aging Neuroscience
#1,557
of 5,200 outputs
Outputs of similar age
#66,938
of 420,630 outputs
Outputs of similar age from Frontiers in Aging Neuroscience
#99
of 365 outputs
Altmetric has tracked 24,334,327 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 5,200 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.2. This one has gotten more attention than average, scoring higher than 68% 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 420,630 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 83% of its contemporaries.
We're also able to compare this research output to 365 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 70% of its contemporaries.