↓ Skip to main content

Deep-learning-based prediction of glaucoma conversion in normotensive glaucoma suspects

Overview of attention for article published in British Journal of Ophthalmology, November 2023
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

news
14 news outlets
blogs
3 blogs
twitter
5 X users
facebook
1 Facebook page

Readers on

mendeley
5 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Deep-learning-based prediction of glaucoma conversion in normotensive glaucoma suspects
Published in
British Journal of Ophthalmology, November 2023
DOI 10.1136/bjo-2022-323167
Pubmed ID
Authors

Ahnul Ha, Sukkyu Sun, Young Kook Kim, Jin Wook Jeoung, Hee Chan Kim, Ki Ho Park

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

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 20%
Researcher 1 20%
Student > Postgraduate 1 20%
Unknown 2 40%
Readers by discipline Count As %
Medicine and Dentistry 2 40%
Computer Science 1 20%
Unknown 2 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 109. 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 22 July 2024.
All research outputs
#408,213
of 26,378,648 outputs
Outputs from British Journal of Ophthalmology
#57
of 6,140 outputs
Outputs of similar age
#7,355
of 374,141 outputs
Outputs of similar age from British Journal of Ophthalmology
#3
of 56 outputs
Altmetric has tracked 26,378,648 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,140 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done particularly well, scoring higher than 99% 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 374,141 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.