The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep learning auto-segmentation of cervical skeletal muscle for sarcopenia analysis in patients with head and neck cancer
|
|---|---|
| Published in |
Frontiers in oncology, July 2022
|
| DOI | 10.3389/fonc.2022.930432 |
| Pubmed ID | |
| Authors |
Mohamed A. Naser, Kareem A. Wahid, Aaron J. Grossberg, Brennan Olson, Rishab Jain, Dina El-Habashy, Cem Dede, Vivian Salama, Moamen Abobakr, Abdallah S. R. Mohamed, Renjie He, Joel Jaskari, Jaakko Sahlsten, Kimmo Kaski, Clifton D. Fuller |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 20% |
| Unknown | 8 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 7 | 70% |
| Members of the public | 2 | 20% |
| Science communicators (journalists, bloggers, editors) | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 32 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 9% |
| Lecturer > Senior Lecturer | 2 | 6% |
| Student > Bachelor | 2 | 6% |
| Researcher | 2 | 6% |
| Student > Master | 2 | 6% |
| Other | 1 | 3% |
| Unknown | 20 | 63% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 5 | 16% |
| Nursing and Health Professions | 2 | 6% |
| Computer Science | 2 | 6% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Sports and Recreations | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 20 | 63% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 03 November 2022.
All research outputs
#6,696,605
of 26,169,168 outputs
Outputs from Frontiers in oncology
#2,202
of 22,913 outputs
Outputs of similar age
#117,662
of 437,817 outputs
Outputs of similar age from Frontiers in oncology
#136
of 1,743 outputs
Altmetric has tracked 26,169,168 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 22,913 research outputs from this source. They receive a mean Attention Score of 3.1. This one has done particularly well, scoring higher than 90% 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 437,817 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 72% of its contemporaries.
We're also able to compare this research output to 1,743 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 92% of its contemporaries.