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Age-specific risk factors for the prediction of obesity using a machine learning approach

Overview of attention for article published in Frontiers in Public Health, January 2023
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

Mentioned by

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2 X users

Citations

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8 Dimensions

Readers on

mendeley
44 Mendeley
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Title
Age-specific risk factors for the prediction of obesity using a machine learning approach
Published in
Frontiers in Public Health, January 2023
DOI 10.3389/fpubh.2022.998782
Pubmed ID
Authors

Junhwi Jeon, Sunmi Lee, Chunyoung Oh

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

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 8 18%
Student > Master 5 11%
Other 4 9%
Student > Postgraduate 3 7%
Unspecified 2 5%
Other 5 11%
Unknown 17 39%
Readers by discipline Count As %
Computer Science 7 16%
Unspecified 5 11%
Engineering 4 9%
Biochemistry, Genetics and Molecular Biology 3 7%
Medicine and Dentistry 3 7%
Other 2 5%
Unknown 20 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 January 2023.
All research outputs
#20,902,742
of 26,557,556 outputs
Outputs from Frontiers in Public Health
#7,525
of 15,029 outputs
Outputs of similar age
#348,167
of 492,711 outputs
Outputs of similar age from Frontiers in Public Health
#530
of 1,263 outputs
Altmetric has tracked 26,557,556 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 15,029 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
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 492,711 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,263 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 51% of its contemporaries.