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Strengthening deep-learning models for intracranial hemorrhage detection: strongly annotated computed tomography images and model ensembles

Overview of attention for article published in Frontiers in Neurology, December 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 (62nd percentile)

Mentioned by

twitter
3 X users

Readers on

mendeley
3 Mendeley
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Title
Strengthening deep-learning models for intracranial hemorrhage detection: strongly annotated computed tomography images and model ensembles
Published in
Frontiers in Neurology, December 2023
DOI 10.3389/fneur.2023.1321964
Pubmed ID
Authors

Dong-Wan Kang, Gi-Hun Park, Wi-Sun Ryu, Dawid Schellingerhout, Museong Kim, Yong Soo Kim, Chan-Young Park, Keon-Joo Lee, Moon-Ku Han, Han-Gil Jeong, Dong-Eog Kim

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

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 33%
Unknown 2 67%
Readers by discipline Count As %
Medicine and Dentistry 1 33%
Unknown 2 67%
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 31 December 2023.
All research outputs
#17,323,426
of 26,208,484 outputs
Outputs from Frontiers in Neurology
#7,230
of 14,901 outputs
Outputs of similar age
#189,765
of 375,435 outputs
Outputs of similar age from Frontiers in Neurology
#193
of 579 outputs
Altmetric has tracked 26,208,484 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,901 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 47th percentile – i.e., 47% 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 375,435 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 579 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 62% of its contemporaries.