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A metric learning approach for endoscopic kidney stone identification

Overview of attention for article published in Expert Systems with Applications, December 2024
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

twitter
5 X users

Readers on

mendeley
4 Mendeley
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Title
A metric learning approach for endoscopic kidney stone identification
Published in
Expert Systems with Applications, December 2024
DOI 10.1016/j.eswa.2024.124711
Authors

Jorge Gonzalez-Zapata, Francisco Lopez-Tiro, Elias Villalvazo-Avila, Daniel Flores-Araiza, Jacques Hubert, Gilberto Ochoa-Ruiz, Christian Daul, Andres Mendez-Vazquez

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 1 25%
Unknown 3 75%
Readers by discipline Count As %
Engineering 1 25%
Unknown 3 75%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 27 July 2024.
All research outputs
#14,930,721
of 26,393,142 outputs
Outputs from Expert Systems with Applications
#1,619
of 4,428 outputs
Outputs of similar age
#1,312
of 2,291 outputs
Outputs of similar age from Expert Systems with Applications
#4
of 18 outputs
Altmetric has tracked 26,393,142 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,428 research outputs from this source. They receive a mean Attention Score of 2.7. This one has gotten more attention than average, scoring higher than 62% 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 2,291 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.