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Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction

Overview of attention for article published in Nature Machine Intelligence, June 2019
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#37 of 340)
  • High Attention Score compared to outputs of the same age (97th percentile)

Mentioned by

news
13 news outlets
blogs
2 blogs
twitter
45 tweeters

Citations

dimensions_citation
83 Dimensions

Readers on

mendeley
100 Mendeley
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Title
Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction
Published in
Nature Machine Intelligence, June 2019
DOI 10.1038/s42256-019-0057-9
Pubmed ID
Authors

Hongming Shan, Atul Padole, Fatemeh Homayounieh, Uwe Kruger, Ruhani Doda Khera, Chayanin Nitiwarangkul, Mannudeep K. Kalra, Ge Wang

Twitter Demographics

The data shown below were collected from the profiles of 45 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 100 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 20%
Researcher 17 17%
Student > Master 11 11%
Student > Bachelor 8 8%
Student > Doctoral Student 5 5%
Other 17 17%
Unknown 22 22%
Readers by discipline Count As %
Computer Science 16 16%
Engineering 16 16%
Medicine and Dentistry 14 14%
Physics and Astronomy 7 7%
Neuroscience 2 2%
Other 12 12%
Unknown 33 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 117. 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 24 May 2021.
All research outputs
#214,930
of 18,017,546 outputs
Outputs from Nature Machine Intelligence
#37
of 340 outputs
Outputs of similar age
#6,997
of 326,049 outputs
Outputs of similar age from Nature Machine Intelligence
#1
of 1 outputs
Altmetric has tracked 18,017,546 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 340 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 60.0. This one has done well, scoring higher than 89% 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 326,049 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 97% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them