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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Evaluation of deep learning-based autosegmentation in breast cancer radiotherapy
|
|---|---|
| Published in |
Radiation Oncology, October 2021
|
| DOI | 10.1186/s13014-021-01923-1 |
| Pubmed ID | |
| Authors |
Hwa Kyung Byun, Jee Suk Chang, Min Seo Choi, Jaehee Chun, Jinhong Jung, Chiyoung Jeong, Jin Sung Kim, Yongjin Chang, Seung Yeun Chung, Seungryul Lee, Yong Bae Kim |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 29% |
| Canada | 1 | 14% |
| Unknown | 4 | 57% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 57% |
| Scientists | 3 | 43% |
Mendeley readers
The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 42 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 10% |
| Other | 3 | 7% |
| Student > Postgraduate | 3 | 7% |
| Professor | 3 | 7% |
| Researcher | 2 | 5% |
| Other | 3 | 7% |
| Unknown | 24 | 57% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 12% |
| Medicine and Dentistry | 5 | 12% |
| Nursing and Health Professions | 2 | 5% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Physics and Astronomy | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 25 | 60% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 17 October 2021.
All research outputs
#7,137,760
of 23,310,485 outputs
Outputs from Radiation Oncology
#368
of 2,092 outputs
Outputs of similar age
#143,108
of 434,666 outputs
Outputs of similar age from Radiation Oncology
#12
of 42 outputs
Altmetric has tracked 23,310,485 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 2,092 research outputs from this source. They receive a mean Attention Score of 2.8. This one has done well, scoring higher than 81% 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 434,666 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 66% 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 gotten more attention than average, scoring higher than 71% of its contemporaries.