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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A state-of-the-art technique to perform cloud-based semantic segmentation using deep learning 3D U-Net architecture
|
|---|---|
| Published in |
BMC Bioinformatics, June 2022
|
| DOI | 10.1186/s12859-022-04794-9 |
| Pubmed ID | |
| Authors |
Zeeshan Shaukat, Qurat ul Ain Farooq, Shanshan Tu, Chuangbai Xiao, Saqib Ali |
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 % |
|---|---|---|
| United States | 1 | 25% |
| India | 1 | 25% |
| Sweden | 1 | 25% |
| United Kingdom | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 26 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Lecturer | 5 | 19% |
| Unspecified | 2 | 8% |
| Student > Ph. D. Student | 2 | 8% |
| Student > Doctoral Student | 1 | 4% |
| Other | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 13 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 3 | 12% |
| Computer Science | 3 | 12% |
| Unspecified | 2 | 8% |
| Biochemistry, Genetics and Molecular Biology | 1 | 4% |
| Linguistics | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 14 | 54% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 26 June 2022.
All research outputs
#15,299,491
of 22,753,345 outputs
Outputs from BMC Bioinformatics
#5,371
of 7,269 outputs
Outputs of similar age
#241,621
of 439,942 outputs
Outputs of similar age from BMC Bioinformatics
#145
of 160 outputs
Altmetric has tracked 22,753,345 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,269 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
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 439,942 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 160 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.