The data shown below were collected from the profiles of 15 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 |
Predicting Age From Brain EEG Signals—A Machine Learning Approach
|
|---|---|
| Published in |
Frontiers in Aging Neuroscience, July 2018
|
| DOI | 10.3389/fnagi.2018.00184 |
| Pubmed ID | |
| Authors |
Obada Al Zoubi, Chung Ki Wong, Rayus T. Kuplicki, Hung-wen Yeh, Ahmad Mayeli, Hazem Refai, Martin Paulus, Jerzy Bodurka |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 20% |
| Germany | 1 | 7% |
| Unknown | 11 | 73% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 73% |
| Scientists | 4 | 27% |
Mendeley readers
The data shown below were compiled from readership statistics for 166 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 166 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 28 | 17% |
| Student > Ph. D. Student | 23 | 14% |
| Student > Master | 23 | 14% |
| Student > Bachelor | 8 | 5% |
| Student > Doctoral Student | 7 | 4% |
| Other | 22 | 13% |
| Unknown | 55 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 30 | 18% |
| Engineering | 19 | 11% |
| Computer Science | 17 | 10% |
| Medicine and Dentistry | 12 | 7% |
| Agricultural and Biological Sciences | 5 | 3% |
| Other | 16 | 10% |
| Unknown | 67 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 10 June 2024.
All research outputs
#4,820,226
of 26,296,035 outputs
Outputs from Frontiers in Aging Neuroscience
#2,390
of 5,669 outputs
Outputs of similar age
#82,808
of 344,877 outputs
Outputs of similar age from Frontiers in Aging Neuroscience
#59
of 103 outputs
Altmetric has tracked 26,296,035 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,669 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.5. This one has gotten more attention than average, scoring higher than 57% 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 344,877 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 75% of its contemporaries.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.