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X Demographics
Mendeley readers
Attention Score in Context
| Title |
RA-UNet: A Hybrid Deep Attention-Aware Network to Extract Liver and Tumor in CT Scans
|
|---|---|
| Published in |
Frontiers in Bioengineering and Biotechnology, December 2020
|
| DOI | 10.3389/fbioe.2020.605132 |
| Pubmed ID | |
| Authors |
Qiangguo Jin, Zhaopeng Meng, Changming Sun, Hui Cui, Ran Su |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 20% |
| Netherlands | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 210 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 210 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 34 | 16% |
| Student > Master | 34 | 16% |
| Researcher | 17 | 8% |
| Student > Doctoral Student | 14 | 7% |
| Student > Bachelor | 9 | 4% |
| Other | 16 | 8% |
| Unknown | 86 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 66 | 31% |
| Engineering | 26 | 12% |
| Neuroscience | 4 | 2% |
| Mathematics | 3 | 1% |
| Agricultural and Biological Sciences | 3 | 1% |
| Other | 14 | 7% |
| Unknown | 94 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 23 December 2020.
All research outputs
#16,057,393
of 25,385,509 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#2,297
of 8,507 outputs
Outputs of similar age
#290,130
of 519,896 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#124
of 335 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,507 research outputs from this source. They receive a mean Attention Score of 3.5. 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 519,896 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 335 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 60% of its contemporaries.