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X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
End-to-End Adversarial Shape Learning for Abdomen Organ Deep Segmentation
|
---|---|
Chapter number | 15 |
Book title |
Machine Learning in Medical Imaging
|
Published in |
arXiv, October 2019
|
DOI | 10.1007/978-3-030-32692-0_15 |
Book ISBNs |
978-3-03-032691-3, 978-3-03-032692-0
|
Authors |
Jinzheng Cai, Yingda Xia, Dong Yang, Daguang Xu, Lin Yang, Holger Roth, Cai, Jinzheng, Xia, Yingda, Yang, Dong, Xu, Daguang, Yang, Lin, Roth, Holger |
X Demographics
The data shown below were collected from the profiles of 15 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 | 3 | 20% |
Australia | 2 | 13% |
Nepal | 1 | 7% |
Netherlands | 1 | 7% |
Unknown | 8 | 53% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 13 | 87% |
Scientists | 1 | 7% |
Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 29 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 6 | 21% |
Student > Master | 4 | 14% |
Researcher | 3 | 10% |
Student > Bachelor | 2 | 7% |
Student > Doctoral Student | 2 | 7% |
Other | 2 | 7% |
Unknown | 10 | 34% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 13 | 45% |
Mathematics | 1 | 3% |
Biochemistry, Genetics and Molecular Biology | 1 | 3% |
Social Sciences | 1 | 3% |
Unknown | 13 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 17 October 2019.
All research outputs
#6,091,187
of 24,093,053 outputs
Outputs from arXiv
#123,034
of 1,018,817 outputs
Outputs of similar age
#105,795
of 357,860 outputs
Outputs of similar age from arXiv
#4,037
of 29,131 outputs
Altmetric has tracked 24,093,053 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,018,817 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 87% 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 357,860 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 29,131 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.