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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep attention super-resolution of brain magnetic resonance images acquired under clinical protocols
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, August 2022
|
| DOI | 10.3389/fncom.2022.887633 |
| Pubmed ID | |
| Authors |
Bryan M. Li, Leonardo V. Castorina, Maria del C. Valdés Hernández, Una Clancy, Stewart J. Wiseman, Eleni Sakka, Amos J. Storkey, Daniela Jaime Garcia, Yajun Cheng, Fergus Doubal, Michael T. Thrippleton, Michael Stringer, Joanna M. Wardlaw |
X Demographics
The data shown below were collected from the profiles of 7 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 | 5 | 71% |
| Unknown | 2 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 71% |
| Scientists | 2 | 29% |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 34 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 15% |
| Lecturer | 3 | 9% |
| Researcher | 3 | 9% |
| Other | 2 | 6% |
| Unspecified | 2 | 6% |
| Other | 4 | 12% |
| Unknown | 15 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 4 | 12% |
| Unspecified | 2 | 6% |
| Business, Management and Accounting | 2 | 6% |
| Engineering | 2 | 6% |
| Psychology | 2 | 6% |
| Other | 5 | 15% |
| Unknown | 17 | 50% |
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 12 September 2022.
All research outputs
#6,375,636
of 25,843,331 outputs
Outputs from Frontiers in Computational Neuroscience
#254
of 1,475 outputs
Outputs of similar age
#111,315
of 431,835 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#6
of 44 outputs
Altmetric has tracked 25,843,331 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,475 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one has done well, scoring higher than 82% 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 431,835 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 74% of its contemporaries.
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 has done well, scoring higher than 86% of its contemporaries.