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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Understanding and Interpreting Machine Learning in Medical Image Computing Applications
|
|---|---|
| Published by |
arXiv, January 2019
|
| DOI | 10.1007/978-3-030-02628-8 |
| ISBNs |
978-3-03-002627-1, 978-3-03-002628-8
|
| Authors |
Sergio Pereira, Raphael Meier, Victor Alves, Mauricio Reyes, Carlos A. Silva |
| Editors |
Stoyanov, Danail, Taylor, Zeike, Kia, Seyed Mostafa, Oguz, Ipek, Reyes, Mauricio, Martel, Anne, Maier-Hein, Lena, Marquand, Andre F., Duchesnay, Edouard, Löfstedt, Tommy, Landman, Bennett, Cardoso, M. Jorge, Silva, Carlos A., Pereira, Sergio, Meier, Raphael |
X Demographics
The data shown below were collected from the profiles of 27 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 5 | 19% |
| India | 2 | 7% |
| United States | 2 | 7% |
| Sweden | 1 | 4% |
| South Africa | 1 | 4% |
| Portugal | 1 | 4% |
| Canada | 1 | 4% |
| Netherlands | 1 | 4% |
| Unknown | 13 | 48% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 18 | 67% |
| Scientists | 7 | 26% |
| Practitioners (doctors, other healthcare professionals) | 2 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 39 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 44% |
| Student > Ph. D. Student | 16 | 41% |
| Student > Master | 14 | 36% |
| Student > Bachelor | 9 | 23% |
| Student > Doctoral Student | 8 | 21% |
| Other | 13 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 34 | 87% |
| Engineering | 25 | 64% |
| Medicine and Dentistry | 3 | 8% |
| Physics and Astronomy | 2 | 5% |
| Neuroscience | 2 | 5% |
| Other | 5 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 28. 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 September 2022.
All research outputs
#1,428,229
of 25,759,158 outputs
Outputs from arXiv
#20,903
of 942,045 outputs
Outputs of similar age
#32,385
of 448,968 outputs
Outputs of similar age from arXiv
#489
of 19,164 outputs
Altmetric has tracked 25,759,158 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 942,045 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 97% 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 448,968 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 92% of its contemporaries.
We're also able to compare this research output to 19,164 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 97% of its contemporaries.