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Practical Use of Regularization in Individualizing a Mathematical Model of Cardiovascular Hemodynamics Using Scarce Data

Overview of attention for article published in Frontiers in Physiology, May 2020
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1 X user

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18 Mendeley
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Title
Practical Use of Regularization in Individualizing a Mathematical Model of Cardiovascular Hemodynamics Using Scarce Data
Published in
Frontiers in Physiology, May 2020
DOI 10.3389/fphys.2020.00452
Pubmed ID
Authors

Ali Tivay, Xin Jin, Alex Kai-Yuan Lo, Christopher G. Scully, Jin-Oh Hahn

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 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 28%
Student > Doctoral Student 3 17%
Researcher 2 11%
Other 1 6%
Professor 1 6%
Other 1 6%
Unknown 5 28%
Readers by discipline Count As %
Engineering 6 33%
Physics and Astronomy 2 11%
Nursing and Health Professions 1 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Biochemistry, Genetics and Molecular Biology 1 6%
Other 1 6%
Unknown 6 33%
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 04 June 2020.
All research outputs
#20,620,796
of 23,211,181 outputs
Outputs from Frontiers in Physiology
#9,593
of 13,961 outputs
Outputs of similar age
#337,839
of 394,737 outputs
Outputs of similar age from Frontiers in Physiology
#329
of 478 outputs
Altmetric has tracked 23,211,181 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 13,961 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. 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 394,737 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 478 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.