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COVID-19 CT image segmentation method based on swin transformer

Overview of attention for article published in Frontiers in Physiology, August 2022
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

twitter
1 X user
patent
1 patent

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
19 Mendeley
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Title
COVID-19 CT image segmentation method based on swin transformer
Published in
Frontiers in Physiology, August 2022
DOI 10.3389/fphys.2022.981463
Pubmed ID
Authors

Weiwei Sun, Jungang Chen, Li Yan, Jinzhao Lin, Yu Pang, Guo Zhang

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 11%
Student > Doctoral Student 2 11%
Unspecified 1 5%
Lecturer > Senior Lecturer 1 5%
Lecturer 1 5%
Other 2 11%
Unknown 10 53%
Readers by discipline Count As %
Medicine and Dentistry 2 11%
Unspecified 1 5%
Computer Science 1 5%
Environmental Science 1 5%
Psychology 1 5%
Other 1 5%
Unknown 12 63%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 30 September 2022.
All research outputs
#7,502,830
of 23,577,654 outputs
Outputs from Frontiers in Physiology
#3,633
of 14,284 outputs
Outputs of similar age
#139,661
of 432,080 outputs
Outputs of similar age from Frontiers in Physiology
#116
of 778 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 14,284 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has gotten more attention than average, scoring higher than 73% 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 432,080 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 67% of its contemporaries.
We're also able to compare this research output to 778 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.