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X Demographics
Mendeley readers
Attention Score in Context
Title |
Deep Learning-Based Concurrent Brain Registration and Tumor Segmentation
|
---|---|
Published in |
Frontiers in Computational Neuroscience, March 2020
|
DOI | 10.3389/fncom.2020.00017 |
Pubmed ID | |
Authors |
Théo Estienne, Marvin Lerousseau, Maria Vakalopoulou, Emilie Alvarez Andres, Enzo Battistella, Alexandre Carré, Siddhartha Chandra, Stergios Christodoulidis, Mihir Sahasrabudhe, Roger Sun, Charlotte Robert, Hugues Talbot, Nikos Paragios, Eric Deutsch |
X Demographics
The data shown below were collected from the profiles of 47 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
India | 5 | 11% |
United States | 3 | 6% |
France | 3 | 6% |
Switzerland | 2 | 4% |
Chile | 1 | 2% |
Brazil | 1 | 2% |
Comoros | 1 | 2% |
Egypt | 1 | 2% |
Germany | 1 | 2% |
Other | 3 | 6% |
Unknown | 26 | 55% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 41 | 87% |
Scientists | 4 | 9% |
Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 67 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 10 | 15% |
Student > Ph. D. Student | 9 | 13% |
Researcher | 6 | 9% |
Student > Bachelor | 6 | 9% |
Lecturer | 4 | 6% |
Other | 8 | 12% |
Unknown | 24 | 36% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 15 | 22% |
Engineering | 10 | 15% |
Medicine and Dentistry | 6 | 9% |
Nursing and Health Professions | 3 | 4% |
Biochemistry, Genetics and Molecular Biology | 2 | 3% |
Other | 6 | 9% |
Unknown | 25 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 26. 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 22 June 2020.
All research outputs
#1,487,839
of 25,622,179 outputs
Outputs from Frontiers in Computational Neuroscience
#53
of 1,472 outputs
Outputs of similar age
#37,580
of 392,197 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#2
of 27 outputs
Altmetric has tracked 25,622,179 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,472 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has done particularly well, scoring higher than 96% 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 392,197 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 27 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 96% of its contemporaries.