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Early-Stage Alzheimer's Disease Prediction Using Machine Learning Models

Overview of attention for article published in Frontiers in Public Health, March 2022
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
5 news outlets
twitter
2 X users

Readers on

mendeley
297 Mendeley
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Title
Early-Stage Alzheimer's Disease Prediction Using Machine Learning Models
Published in
Frontiers in Public Health, March 2022
DOI 10.3389/fpubh.2022.853294
Pubmed ID
Authors

C. Kavitha, Vinodhini Mani, S. R. Srividhya, Osamah Ibrahim Khalaf, Carlos Andrés Tavera Romero

Timeline

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

Geographical breakdown

Country Count As %
Unknown 297 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 34 11%
Student > Ph. D. Student 17 6%
Student > Master 16 5%
Student > Bachelor 11 4%
Researcher 6 2%
Other 22 7%
Unknown 191 64%
Readers by discipline Count As %
Unspecified 34 11%
Computer Science 24 8%
Engineering 11 4%
Neuroscience 6 2%
Agricultural and Biological Sciences 4 1%
Other 22 7%
Unknown 196 66%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 38. 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 24 January 2024.
All research outputs
#1,138,309
of 26,473,472 outputs
Outputs from Frontiers in Public Health
#620
of 14,996 outputs
Outputs of similar age
#27,899
of 456,423 outputs
Outputs of similar age from Frontiers in Public Health
#41
of 969 outputs
Altmetric has tracked 26,473,472 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,996 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has done particularly well, scoring higher than 95% 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 456,423 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 969 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 95% of its contemporaries.