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X Demographics
Mendeley readers
Attention Score in Context
| Title |
DCTclock: Clinically-Interpretable and Automated Artificial Intelligence Analysis of Drawing Behavior for Capturing Cognition
|
|---|---|
| Published in |
Frontiers in Digital Health, October 2021
|
| DOI | 10.3389/fdgth.2021.750661 |
| Pubmed ID | |
| Authors |
William Souillard-Mandar, Dana Penney, Braydon Schaible, Alvaro Pascual-Leone, Rhoda Au, Randall Davis |
X Demographics
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Austria | 1 | 7% |
| Egypt | 1 | 7% |
| United States | 1 | 7% |
| United Kingdom | 1 | 7% |
| Unknown | 11 | 73% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 80% |
| Science communicators (journalists, bloggers, editors) | 2 | 13% |
| Scientists | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 38 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 13% |
| Other | 3 | 8% |
| Researcher | 3 | 8% |
| Student > Doctoral Student | 1 | 3% |
| Student > Bachelor | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 24 | 63% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 5 | 13% |
| Computer Science | 2 | 5% |
| Psychology | 2 | 5% |
| Neuroscience | 2 | 5% |
| Decision Sciences | 1 | 3% |
| Other | 2 | 5% |
| Unknown | 24 | 63% |
Attention Score in Context
This research output has an Altmetric Attention Score of 36. 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 August 2023.
All research outputs
#1,124,160
of 25,432,721 outputs
Outputs from Frontiers in Digital Health
#30
of 831 outputs
Outputs of similar age
#26,396
of 439,038 outputs
Outputs of similar age from Frontiers in Digital Health
#4
of 62 outputs
Altmetric has tracked 25,432,721 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 831 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.9. This one has done particularly well, scoring higher than 96% 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 439,038 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.