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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Evaluation of Enhanced Learning Techniques for Segmenting Ischaemic Stroke Lesions in Brain Magnetic Resonance Perfusion Images Using a Convolutional Neural Network Scheme
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, May 2019
|
| DOI | 10.3389/fninf.2019.00033 |
| Pubmed ID | |
| Authors |
Carlos Uziel Pérez Malla, Maria del C. Valdés Hernández, Muhammad Febrian Rachmadi, Taku Komura |
X Demographics
The data shown below were collected from the profiles of 3 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 | 33% |
| United Kingdom | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 81 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 16% |
| Researcher | 10 | 12% |
| Student > Master | 7 | 9% |
| Other | 5 | 6% |
| Student > Bachelor | 5 | 6% |
| Other | 10 | 12% |
| Unknown | 31 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 12 | 15% |
| Engineering | 10 | 12% |
| Medicine and Dentistry | 9 | 11% |
| Agricultural and Biological Sciences | 3 | 4% |
| Neuroscience | 3 | 4% |
| Other | 8 | 10% |
| Unknown | 36 | 44% |
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 30 May 2019.
All research outputs
#14,876,223
of 23,798,792 outputs
Outputs from Frontiers in Neuroinformatics
#500
of 779 outputs
Outputs of similar age
#194,426
of 352,140 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#12
of 21 outputs
Altmetric has tracked 23,798,792 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 779 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 32nd percentile – i.e., 32% 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 352,140 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 21 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.