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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Training machine learning models with synthetic data improves the prediction of ventricular origin in outflow tract ventricular arrhythmias
|
|---|---|
| Published in |
Frontiers in Physiology, August 2022
|
| DOI | 10.3389/fphys.2022.909372 |
| Pubmed ID | |
| Authors |
Ruben Doste, Miguel Lozano, Guillermo Jimenez-Perez, Lluis Mont, Antonio Berruezo, Diego Penela, Oscar Camara, Rafael Sebastian |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 50% |
| Switzerland | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 22% |
| Researcher | 4 | 17% |
| Student > Doctoral Student | 3 | 13% |
| Lecturer > Senior Lecturer | 1 | 4% |
| Professor | 1 | 4% |
| Other | 3 | 13% |
| Unknown | 6 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 5 | 22% |
| Computer Science | 4 | 17% |
| Nursing and Health Professions | 2 | 9% |
| Unspecified | 1 | 4% |
| Medicine and Dentistry | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 9 | 39% |
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 22 September 2022.
All research outputs
#19,231,808
of 24,489,824 outputs
Outputs from Frontiers in Physiology
#7,850
of 15,056 outputs
Outputs of similar age
#292,497
of 421,890 outputs
Outputs of similar age from Frontiers in Physiology
#358
of 748 outputs
Altmetric has tracked 24,489,824 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 15,056 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one is in the 40th percentile – i.e., 40% 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 421,890 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 748 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.