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Prediction of Left Ventricular Mechanics Using Machine Learning

Overview of attention for article published in Frontiers in Physics, September 2019
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Mentioned by

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1 X user

Citations

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39 Dimensions

Readers on

mendeley
72 Mendeley
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Title
Prediction of Left Ventricular Mechanics Using Machine Learning
Published in
Frontiers in Physics, September 2019
DOI 10.3389/fphy.2019.00117
Pubmed ID
Authors

Yaghoub Dabiri, Alex Van der Velden, Kevin L. Sack, Jenny S. Choy, Ghassan S. Kassab, Julius M. Guccione

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 72 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 17%
Student > Master 10 14%
Researcher 8 11%
Student > Bachelor 5 7%
Student > Doctoral Student 4 6%
Other 9 13%
Unknown 24 33%
Readers by discipline Count As %
Engineering 22 31%
Medicine and Dentistry 5 7%
Computer Science 4 6%
Biochemistry, Genetics and Molecular Biology 2 3%
Physics and Astronomy 2 3%
Other 7 10%
Unknown 30 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 06 September 2019.
All research outputs
#20,578,452
of 23,155,957 outputs
Outputs from Frontiers in Physics
#1,645
of 3,625 outputs
Outputs of similar age
#289,572
of 340,571 outputs
Outputs of similar age from Frontiers in Physics
#22
of 44 outputs
Altmetric has tracked 23,155,957 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,625 research outputs from this source. They receive a mean Attention Score of 2.5. This one is in the 1st percentile – i.e., 1% 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 340,571 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.