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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A deep image-to-image network organ segmentation algorithm for radiation treatment planning: principles and evaluation
|
|---|---|
| Published in |
Radiation Oncology, July 2022
|
| DOI | 10.1186/s13014-022-02102-6 |
| Pubmed ID | |
| Authors |
Sebastian Marschner, Manasi Datar, Aurélie Gaasch, Zhoubing Xu, Sasa Grbic, Guillaume Chabin, Bernhard Geiger, Julian Rosenman, Stefanie Corradini, Maximilian Niyazi, Tobias Heimann, Christian Möhler, Fernando Vega, Claus Belka, Christian Thieke |
X Demographics
The data shown below were collected from the profiles of 4 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 | 2 | 50% |
| United States | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 20% |
| Student > Ph. D. Student | 2 | 13% |
| Professor > Associate Professor | 2 | 13% |
| Student > Master | 1 | 7% |
| Unknown | 7 | 47% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 27% |
| Physics and Astronomy | 2 | 13% |
| Computer Science | 2 | 13% |
| Unknown | 7 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 28 July 2022.
All research outputs
#13,817,193
of 23,868,920 outputs
Outputs from Radiation Oncology
#605
of 2,131 outputs
Outputs of similar age
#171,285
of 420,867 outputs
Outputs of similar age from Radiation Oncology
#11
of 42 outputs
Altmetric has tracked 23,868,920 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,131 research outputs from this source. They receive a mean Attention Score of 2.9. This one has gotten more attention than average, scoring higher than 70% 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 420,867 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 58% of its contemporaries.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.