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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A Comparison of Fully-Coupled 3D In-Stent Restenosis Simulations to In-vivo Data
|
|---|---|
| Published in |
Frontiers in Physiology, May 2017
|
| DOI | 10.3389/fphys.2017.00284 |
| Pubmed ID | |
| Authors |
Pavel S. Zun, Tatiana Anikina, Andrew Svitenkov, Alfons G. Hoekstra |
| Abstract |
We describe our fully-coupled 3D multiscale model of in-stent restenosis, with blood flow simulations coupled to smooth muscle cell proliferation, and report results of numerical simulations performed with this model. This novel model is based on several previously reported 2D models. We study the effects of various parameters on the process of restenosis and compare with in vivo porcine data where we observe good qualitative agreement. We study the effects of stent deployment depth (and related injury score), reendothelization speed, and simulate the effect of stent width. Also we demonstrate that we are now capable to simulate restenosis in real-sized (18 mm long, 2.8 mm wide) vessel geometries. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 20% |
| Switzerland | 1 | 20% |
| United Kingdom | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 48 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 9 | 19% |
| Researcher | 6 | 13% |
| Student > Ph. D. Student | 5 | 10% |
| Other | 4 | 8% |
| Professor > Associate Professor | 4 | 8% |
| Other | 7 | 15% |
| Unknown | 13 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 12 | 25% |
| Computer Science | 4 | 8% |
| Biochemistry, Genetics and Molecular Biology | 3 | 6% |
| Medicine and Dentistry | 3 | 6% |
| Chemistry | 2 | 4% |
| Other | 5 | 10% |
| Unknown | 19 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 25 May 2017.
All research outputs
#6,958,146
of 22,973,051 outputs
Outputs from Frontiers in Physiology
#3,303
of 13,723 outputs
Outputs of similar age
#110,023
of 313,686 outputs
Outputs of similar age from Frontiers in Physiology
#72
of 259 outputs
Altmetric has tracked 22,973,051 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 13,723 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done well, scoring higher than 75% 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 313,686 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 259 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 71% of its contemporaries.