| Title |
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning
|
|---|---|
| Published in |
Nature Machine Intelligence, September 2021
|
| DOI | 10.1038/s42256-021-00390-3 |
| Authors |
Dmitrii Usynin, Alexander Ziller, Marcus Makowski, Rickmer Braren, Daniel Rueckert, Ben Glocker, Georgios Kaissis, Jonathan Passerat-Palmbach |
X Demographics
The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 3 | 25% |
| Germany | 3 | 25% |
| United States | 1 | 8% |
| Unknown | 5 | 42% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 75% |
| Practitioners (doctors, other healthcare professionals) | 2 | 17% |
| Scientists | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 36 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 25% |
| Student > Master | 5 | 14% |
| Researcher | 3 | 8% |
| Other | 3 | 8% |
| Unspecified | 2 | 6% |
| Other | 6 | 17% |
| Unknown | 8 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 13 | 36% |
| Engineering | 5 | 14% |
| Unspecified | 2 | 6% |
| Biochemistry, Genetics and Molecular Biology | 2 | 6% |
| Social Sciences | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 10 | 28% |
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 21 September 2021.
All research outputs
#4,168,443
of 23,318,744 outputs
Outputs from Nature Machine Intelligence
#424
of 580 outputs
Outputs of similar age
#91,052
of 433,304 outputs
Outputs of similar age from Nature Machine Intelligence
#23
of 30 outputs
Altmetric has tracked 23,318,744 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 580 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 65.7. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
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 433,304 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 78% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.