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Exploring potential barriers in equitable access to pediatric diagnostic imaging using machine learning

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

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
3 X users

Readers on

mendeley
8 Mendeley
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Title
Exploring potential barriers in equitable access to pediatric diagnostic imaging using machine learning
Published in
Frontiers in Public Health, February 2023
DOI 10.3389/fpubh.2023.968319
Pubmed ID
Authors

Maryam Taheri-Shirazi, Khashayar Namdar, Kelvin Ling, Karima Karmali, Melissa D. McCradden, Wayne Lee, Farzad Khalvati

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 25%
Researcher 1 13%
Student > Master 1 13%
Unknown 4 50%
Readers by discipline Count As %
Unspecified 2 25%
Unknown 6 75%
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 23 March 2023.
All research outputs
#16,236,285
of 23,924,883 outputs
Outputs from Frontiers in Public Health
#5,325
of 11,786 outputs
Outputs of similar age
#234,415
of 406,864 outputs
Outputs of similar age from Frontiers in Public Health
#416
of 1,231 outputs
Altmetric has tracked 23,924,883 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,786 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has gotten more attention than average, scoring higher than 50% 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 406,864 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,231 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 63% of its contemporaries.