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Using Machine Learning and the National Health and Nutrition Examination Survey to Classify Individuals With Hearing Loss

Overview of attention for article published in Frontiers in Digital Health, August 2021
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 X users

Citations

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3 Dimensions

Readers on

mendeley
28 Mendeley
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Title
Using Machine Learning and the National Health and Nutrition Examination Survey to Classify Individuals With Hearing Loss
Published in
Frontiers in Digital Health, August 2021
DOI 10.3389/fdgth.2021.723533
Pubmed ID
Authors

Gregory M. Ellis, Pamela E. Souza

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

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 11%
Lecturer 2 7%
Researcher 2 7%
Student > Master 2 7%
Student > Doctoral Student 1 4%
Other 3 11%
Unknown 15 54%
Readers by discipline Count As %
Medicine and Dentistry 4 14%
Computer Science 2 7%
Business, Management and Accounting 2 7%
Nursing and Health Professions 1 4%
Social Sciences 1 4%
Other 3 11%
Unknown 15 54%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 21 August 2021.
All research outputs
#15,025,659
of 23,310,485 outputs
Outputs from Frontiers in Digital Health
#405
of 579 outputs
Outputs of similar age
#229,638
of 432,543 outputs
Outputs of similar age from Frontiers in Digital Health
#50
of 65 outputs
Altmetric has tracked 23,310,485 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 579 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.4. This one is in the 29th percentile – i.e., 29% 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 432,543 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.