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Digital twins to personalize medicine

Overview of attention for article published in Genome Medicine, December 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 (96th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

news
5 news outlets
twitter
31 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
190 Dimensions

Readers on

mendeley
326 Mendeley
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Title
Digital twins to personalize medicine
Published in
Genome Medicine, December 2019
DOI 10.1186/s13073-019-0701-3
Pubmed ID
Authors

Bergthor Björnsson, Carl Borrebaeck, Nils Elander, Thomas Gasslander, Danuta R. Gawel, Mika Gustafsson, Rebecka Jörnsten, Eun Jung Lee, Xinxiu Li, Sandra Lilja, David Martínez-Enguita, Andreas Matussek, Per Sandström, Samuel Schäfer, Margaretha Stenmarker, X. F. Sun, Oleg Sysoev, Huan Zhang, Mikael Benson

X Demographics

X Demographics

The data shown below were collected from the profiles of 31 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 326 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 326 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 49 15%
Student > Ph. D. Student 48 15%
Student > Master 29 9%
Student > Bachelor 23 7%
Unspecified 13 4%
Other 53 16%
Unknown 111 34%
Readers by discipline Count As %
Engineering 46 14%
Computer Science 30 9%
Biochemistry, Genetics and Molecular Biology 25 8%
Medicine and Dentistry 24 7%
Unspecified 13 4%
Other 64 20%
Unknown 124 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 53. 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 01 February 2024.
All research outputs
#798,608
of 25,378,284 outputs
Outputs from Genome Medicine
#152
of 1,584 outputs
Outputs of similar age
#19,035
of 470,532 outputs
Outputs of similar age from Genome Medicine
#5
of 32 outputs
Altmetric has tracked 25,378,284 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,584 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.8. This one has done particularly well, scoring higher than 90% 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 470,532 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 96% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.