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DeepStrain: A Deep Learning Workflow for the Automated Characterization of Cardiac Mechanics

Overview of attention for article published in Frontiers in Cardiovascular Medicine, September 2021
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

twitter
13 X users

Readers on

mendeley
67 Mendeley
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Title
DeepStrain: A Deep Learning Workflow for the Automated Characterization of Cardiac Mechanics
Published in
Frontiers in Cardiovascular Medicine, September 2021
DOI 10.3389/fcvm.2021.730316
Pubmed ID
Authors

Manuel A. Morales, Maaike van den Boomen, Christopher Nguyen, Jayashree Kalpathy-Cramer, Bruce R. Rosen, Collin M. Stultz, David Izquierdo-Garcia, Ciprian Catana

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 13 X users 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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 21%
Researcher 11 16%
Professor > Associate Professor 5 7%
Student > Doctoral Student 4 6%
Lecturer 4 6%
Other 11 16%
Unknown 18 27%
Readers by discipline Count As %
Computer Science 17 25%
Medicine and Dentistry 11 16%
Engineering 9 13%
Agricultural and Biological Sciences 3 4%
Physics and Astronomy 2 3%
Other 2 3%
Unknown 23 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 02 November 2021.
All research outputs
#3,719,199
of 23,310,485 outputs
Outputs from Frontiers in Cardiovascular Medicine
#485
of 7,209 outputs
Outputs of similar age
#81,222
of 429,465 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#41
of 608 outputs
Altmetric has tracked 23,310,485 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,209 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 93% 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 429,465 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 608 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.