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Failure Detection in Deep Neural Networks for Medical Imaging

Overview of attention for article published in Frontiers in Medical Technology, July 2022
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About this Attention Score

  • Among the highest-scoring outputs from this source (#41 of 261)
  • Good Attention Score compared to outputs of the same age (71st percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

twitter
7 X users

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
10 Mendeley
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Title
Failure Detection in Deep Neural Networks for Medical Imaging
Published in
Frontiers in Medical Technology, July 2022
DOI 10.3389/fmedt.2022.919046
Pubmed ID
Authors

Sabeen Ahmed, Dimah Dera, Saud Ul Hassan, Nidhal Bouaynaya, Ghulam Rasool

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 2 20%
Researcher 1 10%
Student > Postgraduate 1 10%
Student > Doctoral Student 1 10%
Unknown 5 50%
Readers by discipline Count As %
Engineering 4 40%
Computer Science 1 10%
Unknown 5 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 14 September 2022.
All research outputs
#6,552,941
of 24,417,958 outputs
Outputs from Frontiers in Medical Technology
#41
of 261 outputs
Outputs of similar age
#117,867
of 423,108 outputs
Outputs of similar age from Frontiers in Medical Technology
#5
of 32 outputs
Altmetric has tracked 24,417,958 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 261 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one has done well, scoring higher than 84% 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 423,108 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.