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Enabling supra-aortic vessels inclusion in statistical shape models of the aorta: a novel non-rigid registration method

Overview of attention for article published in Frontiers in Physiology, August 2023
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
6 Mendeley
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Title
Enabling supra-aortic vessels inclusion in statistical shape models of the aorta: a novel non-rigid registration method
Published in
Frontiers in Physiology, August 2023
DOI 10.3389/fphys.2023.1211461
Pubmed ID
Authors

Martino Andrea Scarpolini, Marilena Mazzoli, Simona Celi

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Other 1 17%
Student > Master 1 17%
Unknown 4 67%
Readers by discipline Count As %
Medicine and Dentistry 2 33%
Unknown 4 67%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 25 August 2023.
All research outputs
#13,617,955
of 24,329,306 outputs
Outputs from Frontiers in Physiology
#4,210
of 14,927 outputs
Outputs of similar age
#78,498
of 222,678 outputs
Outputs of similar age from Frontiers in Physiology
#37
of 302 outputs
Altmetric has tracked 24,329,306 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,927 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one has gotten more attention than average, scoring higher than 71% 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 222,678 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 65% of its contemporaries.
We're also able to compare this research output to 302 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.