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X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images
|
---|---|
Chapter number | 16 |
Book title |
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries
|
Published in |
arXiv, September 2018
|
DOI | 10.1007/978-3-030-11723-8_16 |
Book ISBNs |
978-3-03-011722-1, 978-3-03-011723-8
|
Authors |
Christoph Baur, Benedikt Wiestler, Shadi Albarqouni, Nassir Navab, Baur, Christoph, Wiestler, Benedikt, Albarqouni, Shadi, Navab, Nassir |
X Demographics
The data shown below were collected from the profiles of 20 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 | 2 | 10% |
Turkey | 2 | 10% |
Germany | 2 | 10% |
South Africa | 1 | 5% |
United Kingdom | 1 | 5% |
Canada | 1 | 5% |
Unknown | 11 | 55% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 17 | 85% |
Scientists | 3 | 15% |
Mendeley readers
The data shown below were compiled from readership statistics for 383 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 383 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 93 | 24% |
Student > Master | 74 | 19% |
Researcher | 43 | 11% |
Student > Bachelor | 22 | 6% |
Student > Doctoral Student | 15 | 4% |
Other | 31 | 8% |
Unknown | 105 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 155 | 40% |
Engineering | 63 | 16% |
Medicine and Dentistry | 11 | 3% |
Physics and Astronomy | 7 | 2% |
Agricultural and Biological Sciences | 5 | 1% |
Other | 24 | 6% |
Unknown | 118 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. 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 20 June 2022.
All research outputs
#1,996,291
of 24,002,307 outputs
Outputs from arXiv
#33,591
of 1,011,770 outputs
Outputs of similar age
#39,413
of 314,636 outputs
Outputs of similar age from arXiv
#800
of 24,509 outputs
Altmetric has tracked 24,002,307 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,011,770 research outputs from this source. They receive a mean Attention Score of 4.0. 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 314,636 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 24,509 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.