The data shown below were collected from the profiles of 22 X users who shared this research output. Click here to find out more about how the information was compiled.
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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep Learning Convolutional Neural Networks Discriminate Adult ADHD From Healthy Individuals on the Basis of Event-Related Spectral EEG
|
|---|---|
| Published in |
Frontiers in Neuroscience, April 2020
|
| DOI | 10.3389/fnins.2020.00251 |
| Pubmed ID | |
| Authors |
Laura Dubreuil-Vall, Giulio Ruffini, Joan A. Camprodon |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 14% |
| Spain | 2 | 9% |
| Unknown | 17 | 77% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 13 | 59% |
| Scientists | 5 | 23% |
| Practitioners (doctors, other healthcare professionals) | 3 | 14% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 163 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 163 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 21 | 13% |
| Researcher | 18 | 11% |
| Unspecified | 15 | 9% |
| Student > Ph. D. Student | 12 | 7% |
| Student > Bachelor | 9 | 6% |
| Other | 28 | 17% |
| Unknown | 60 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 19 | 12% |
| Engineering | 17 | 10% |
| Computer Science | 16 | 10% |
| Unspecified | 15 | 9% |
| Psychology | 11 | 7% |
| Other | 16 | 10% |
| Unknown | 69 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 23. 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 13 November 2023.
All research outputs
#1,716,570
of 26,456,908 outputs
Outputs from Frontiers in Neuroscience
#835
of 11,883 outputs
Outputs of similar age
#43,524
of 405,336 outputs
Outputs of similar age from Frontiers in Neuroscience
#35
of 346 outputs
Altmetric has tracked 26,456,908 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,883 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.2. This one has done particularly well, scoring higher than 92% 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 405,336 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 346 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.