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Twitter Demographics
Mendeley readers
Attention Score in Context
| Title |
Learn-Morph-Infer: A new way of solving the inverse problem for brain tumor modeling
|
|---|---|
| Published in |
Medical Image Analysis, January 2023
|
| DOI | 10.1016/j.media.2022.102672 |
| Authors |
Ivan Ezhov, Kevin Scibilia, Katharina Franitza, Felix Steinbauer, Suprosanna Shit, Lucas Zimmer, Jana Lipkova, Florian Kofler, Johannes C. Paetzold, Luca Canalini, Diana Waldmannstetter, Martin J. Menten, Marie Metz, Benedikt Wiestler, Bjoern Menze |
Twitter Demographics
The data shown below were collected from the profiles of 16 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 2 | 13% |
| United Kingdom | 2 | 13% |
| Germany | 2 | 13% |
| Italy | 1 | 6% |
| Belgium | 1 | 6% |
| Unknown | 8 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 75% |
| Scientists | 4 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 26% |
| Student > Bachelor | 2 | 11% |
| Researcher | 2 | 11% |
| Professor > Associate Professor | 2 | 11% |
| Student > Master | 1 | 5% |
| Other | 3 | 16% |
| Unknown | 4 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 6 | 32% |
| Mathematics | 3 | 16% |
| Engineering | 3 | 16% |
| Medicine and Dentistry | 1 | 5% |
| Unspecified | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 5 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 25 December 2022.
All research outputs
#2,528,767
of 23,415,749 outputs
Outputs from Medical Image Analysis
#75
of 1,504 outputs
Outputs of similar age
#48,723
of 429,922 outputs
Outputs of similar age from Medical Image Analysis
#2
of 44 outputs
Altmetric has tracked 23,415,749 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,504 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done particularly well, scoring higher than 95% 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 429,922 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 88% of its contemporaries.
We're also able to compare this research output to 44 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.