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An inline deep learning based free-breathing ECG-free cine for exercise cardiovascular magnetic resonance

Overview of attention for article published in Critical Reviews in Diagnostic Imaging, August 2022
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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 (78th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

twitter
12 X users

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
20 Mendeley
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Title
An inline deep learning based free-breathing ECG-free cine for exercise cardiovascular magnetic resonance
Published in
Critical Reviews in Diagnostic Imaging, August 2022
DOI 10.1186/s12968-022-00879-9
Pubmed ID
Authors

Manuel A. Morales, Salah Assana, Xiaoying Cai, Kelvin Chow, Hassan Haji-valizadeh, Eiryu Sai, Connie Tsao, Jason Matos, Jennifer Rodriguez, Sophie Berg, Neal Whitehead, Patrick Pierce, Beth Goddu, Warren J. Manning, Reza Nezafat

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 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 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 25%
Researcher 2 10%
Student > Bachelor 1 5%
Professor 1 5%
Student > Master 1 5%
Other 3 15%
Unknown 7 35%
Readers by discipline Count As %
Engineering 8 40%
Medicine and Dentistry 2 10%
Biochemistry, Genetics and Molecular Biology 1 5%
Unspecified 1 5%
Business, Management and Accounting 1 5%
Other 0 0%
Unknown 7 35%
Attention Score in Context

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 18 September 2022.
All research outputs
#4,629,251
of 25,523,622 outputs
Outputs from Critical Reviews in Diagnostic Imaging
#285
of 1,379 outputs
Outputs of similar age
#91,368
of 432,343 outputs
Outputs of similar age from Critical Reviews in Diagnostic Imaging
#5
of 12 outputs
Altmetric has tracked 25,523,622 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 1,379 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has done well, scoring higher than 79% 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 432,343 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 78% of its contemporaries.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.