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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using Machine Learning to Characterize Atrial Fibrotic Substrate From Intracardiac Signals With a Hybrid in silico and in vivo Dataset
|
|---|---|
| Published in |
Frontiers in Physiology, July 2021
|
| DOI | 10.3389/fphys.2021.699291 |
| Pubmed ID | |
| Authors |
Jorge Sánchez, Giorgio Luongo, Mark Nothstein, Laura A. Unger, Javier Saiz, Beatriz Trenor, Armin Luik, Olaf Dössel, Axel Loewe |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 13% |
| Spain | 1 | 13% |
| Germany | 1 | 13% |
| United States | 1 | 13% |
| Switzerland | 1 | 13% |
| Unknown | 3 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 88% |
| Scientists | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 26 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 19% |
| Other | 4 | 15% |
| Student > Master | 3 | 12% |
| Professor | 3 | 12% |
| Student > Postgraduate | 2 | 8% |
| Other | 3 | 12% |
| Unknown | 6 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 11 | 42% |
| Computer Science | 2 | 8% |
| Medicine and Dentistry | 2 | 8% |
| Agricultural and Biological Sciences | 1 | 4% |
| Biochemistry, Genetics and Molecular Biology | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 9 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 July 2021.
All research outputs
#5,831,679
of 23,308,124 outputs
Outputs from Frontiers in Physiology
#2,678
of 14,041 outputs
Outputs of similar age
#120,253
of 439,888 outputs
Outputs of similar age from Frontiers in Physiology
#88
of 634 outputs
Altmetric has tracked 23,308,124 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 14,041 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 80% 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 439,888 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 72% of its contemporaries.
We're also able to compare this research output to 634 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.