The data shown below were collected from the profiles of 18 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 |
GANterfactual—Counterfactual Explanations for Medical Non-experts Using Generative Adversarial Learning
|
|---|---|
| Published in |
arXiv, April 2022
|
| DOI | 10.3389/frai.2022.825565 |
| Pubmed ID | |
| Authors |
Silvan Mertes, Tobias Huber, Katharina Weitz, Alexander Heimerl, Elisabeth André |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 17% |
| Switzerland | 1 | 6% |
| Netherlands | 1 | 6% |
| Japan | 1 | 6% |
| Unknown | 12 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 13 | 72% |
| Scientists | 4 | 22% |
| Practitioners (doctors, other healthcare professionals) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 57 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 14% |
| Student > Ph. D. Student | 7 | 12% |
| Researcher | 4 | 7% |
| Student > Doctoral Student | 3 | 5% |
| Other | 3 | 5% |
| Other | 4 | 7% |
| Unknown | 28 | 49% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 13 | 23% |
| Business, Management and Accounting | 4 | 7% |
| Engineering | 2 | 4% |
| Nursing and Health Professions | 2 | 4% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Other | 4 | 7% |
| Unknown | 31 | 54% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 08 April 2022.
All research outputs
#5,286,844
of 25,387,668 outputs
Outputs from arXiv
#91,495
of 915,148 outputs
Outputs of similar age
#113,989
of 448,289 outputs
Outputs of similar age from arXiv
#2,960
of 28,368 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 915,148 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 89% 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 448,289 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 28,368 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.