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Adopting machine learning to automatically identify candidate patients for corneal refractive surgery

Overview of attention for article published in npj Digital Medicine, June 2019
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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 (95th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

Mentioned by

news
3 news outlets
twitter
51 X users
patent
1 patent

Citations

dimensions_citation
52 Dimensions

Readers on

mendeley
62 Mendeley
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Title
Adopting machine learning to automatically identify candidate patients for corneal refractive surgery
Published in
npj Digital Medicine, June 2019
DOI 10.1038/s41746-019-0135-8
Pubmed ID
Authors

Tae Keun Yoo, Ik Hee Ryu, Geunyoung Lee, Youngnam Kim, Jin Kuk Kim, In Sik Lee, Jung Sub Kim, Tyler Hyungtaek Rim

X Demographics

X Demographics

The data shown below were collected from the profiles of 51 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 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 62 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 18%
Student > Bachelor 7 11%
Student > Ph. D. Student 7 11%
Student > Master 6 10%
Student > Doctoral Student 5 8%
Other 10 16%
Unknown 16 26%
Readers by discipline Count As %
Medicine and Dentistry 17 27%
Engineering 5 8%
Computer Science 4 6%
Chemistry 3 5%
Physics and Astronomy 3 5%
Other 9 15%
Unknown 21 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 57. 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 20 November 2023.
All research outputs
#747,475
of 25,382,035 outputs
Outputs from npj Digital Medicine
#226
of 974 outputs
Outputs of similar age
#16,079
of 359,014 outputs
Outputs of similar age from npj Digital Medicine
#17
of 37 outputs
Altmetric has tracked 25,382,035 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 974 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.8. This one has done well, scoring higher than 76% 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 359,014 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 95% of its contemporaries.
We're also able to compare this research output to 37 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 56% of its contemporaries.