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Explaining decisions of graph convolutional neural networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer

Overview of attention for article published in Genome Medicine, March 2021
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (73rd percentile)

Mentioned by

twitter
11 tweeters

Citations

dimensions_citation
20 Dimensions

Readers on

mendeley
97 Mendeley
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Title
Explaining decisions of graph convolutional neural networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer
Published in
Genome Medicine, March 2021
DOI 10.1186/s13073-021-00845-7
Pubmed ID
Authors

Hryhorii Chereda, Annalen Bleckmann, Kerstin Menck, Júlia Perera-Bel, Philip Stegmaier, Florian Auer, Frank Kramer, Andreas Leha, Tim Beißbarth

Twitter Demographics

The data shown below were collected from the profiles of 11 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 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 97 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 14%
Student > Master 13 13%
Student > Ph. D. Student 10 10%
Other 7 7%
Student > Doctoral Student 5 5%
Other 13 13%
Unknown 35 36%
Readers by discipline Count As %
Computer Science 18 19%
Engineering 10 10%
Biochemistry, Genetics and Molecular Biology 9 9%
Agricultural and Biological Sciences 4 4%
Medicine and Dentistry 4 4%
Other 13 13%
Unknown 39 40%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 27 June 2022.
All research outputs
#3,990,346
of 22,103,655 outputs
Outputs from Genome Medicine
#808
of 1,401 outputs
Outputs of similar age
#100,364
of 377,112 outputs
Outputs of similar age from Genome Medicine
#2
of 2 outputs
Altmetric has tracked 22,103,655 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,401 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.5. This one is in the 42nd percentile – i.e., 42% 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 377,112 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 73% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.