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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Semantic Context Forests for Learning-Based Knee Cartilage Segmentation
in 3D MR Images
|
|---|---|
| Chapter number | 11 |
| Book title |
Medical Computer Vision. Large Data in Medical Imaging
|
| Published in |
arXiv, July 2013
|
| DOI | 10.1007/978-3-319-05530-5_11 |
| Book ISBNs |
978-3-31-905529-9, 978-3-31-905530-5
|
| Authors |
Quan Wang, Dijia Wu, Le Lu, Meizhu Liu, Kim L. Boyer, Shaohua Kevin Zhou, Wang, Quan, Wu, Dijia, Lu, Le, Liu, Meizhu, Boyer, Kim L., Zhou, Shaohua Kevin |
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 % |
|---|---|---|
| Norway | 1 | 25% |
| Chile | 1 | 25% |
| Philippines | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 3% |
| Colombia | 1 | 3% |
| Sweden | 1 | 3% |
| Unknown | 37 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 33% |
| Researcher | 7 | 18% |
| Student > Master | 6 | 15% |
| Student > Bachelor | 5 | 13% |
| Lecturer | 2 | 5% |
| Other | 6 | 15% |
| Unknown | 1 | 3% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 19 | 48% |
| Engineering | 17 | 43% |
| Medicine and Dentistry | 1 | 3% |
| Unspecified | 1 | 3% |
| Unknown | 2 | 5% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 07 November 2017.
All research outputs
#4,418,776
of 24,002,307 outputs
Outputs from arXiv
#104,743
of 1,011,770 outputs
Outputs of similar age
#36,049
of 197,818 outputs
Outputs of similar age from arXiv
#454
of 8,853 outputs
Altmetric has tracked 24,002,307 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% 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 well, scoring higher than 89% 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 197,818 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 81% of its contemporaries.
We're also able to compare this research output to 8,853 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 94% of its contemporaries.