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A feasibility study of deep learning for predicting hemodynamics of human thoracic aorta

Overview of attention for article published in Journal of Biomechanics, November 2019
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Mentioned by

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6 X users

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mendeley
186 Mendeley
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Article details
Title
A feasibility study of deep learning for predicting hemodynamics of human thoracic aorta
Published in
Journal of Biomechanics, November 2019
DOI 10.1016/j.jbiomech.2019.109544
Pubmed ID
Authors

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Timeline Attention over time Attention Score history
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Activity
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X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 186 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 186 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 29 16%
Student > Master 16 9%
Student > Doctoral Student 14 8%
Researcher 13 7%
Student > Bachelor 10 5%
Other 18 10%
Unknown 86 46%
Readers by discipline
Readers by discipline Count As %
Engineering 56 30%
Medicine and Dentistry 7 4%
Computer Science 6 3%
Social Sciences 3 2%
Biochemistry, Genetics and Molecular Biology 2 1%
Other 16 9%
Unknown 96 52%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 11 July 2022.
All research outputs
#15,179,141
of 25,387,668 outputs
Outputs from Journal of Biomechanics
#3,702
of 5,358 outputs
Outputs of similar age
#245,023
of 473,607 outputs
Outputs of similar age from Journal of Biomechanics
#100
of 132 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,358 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one is in the 29th percentile – i.e., 29% 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 473,607 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 132 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.