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Twitter Demographics
Mendeley readers
Attention Score in Context
Chapter title |
Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory and Practice
|
---|---|
Chapter number | 11 |
Book title |
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
|
Published in |
arXiv, October 2019
|
DOI | 10.1007/978-3-030-32245-8_11 |
Book ISBNs |
978-3-03-032244-1, 978-3-03-032245-8
|
Authors |
Jeroen Bertels, Tom Eelbode, Maxim Berman, Dirk Vandermeulen, Frederik Maes, Raf Bisschops, Matthew B. Blaschko, Matthew Blaschko, Bertels, Jeroen, Eelbode, Tom, Berman, Maxim, Vandermeulen, Dirk, Maes, Frederik, Bisschops, Raf, Blaschko, Matthew B. |
Twitter Demographics
The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Japan | 1 | 17% |
Netherlands | 1 | 17% |
Unknown | 4 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 83% |
Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 200 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 200 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 34 | 17% |
Student > Master | 25 | 13% |
Student > Bachelor | 24 | 12% |
Researcher | 13 | 7% |
Student > Doctoral Student | 6 | 3% |
Other | 26 | 13% |
Unknown | 72 | 36% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 39 | 20% |
Computer Science | 37 | 19% |
Medicine and Dentistry | 9 | 5% |
Agricultural and Biological Sciences | 5 | 3% |
Unspecified | 3 | 2% |
Other | 19 | 10% |
Unknown | 88 | 44% |
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 13 September 2022.
All research outputs
#5,086,107
of 24,099,692 outputs
Outputs from arXiv
#114,681
of 1,020,419 outputs
Outputs of similar age
#98,595
of 357,905 outputs
Outputs of similar age from arXiv
#3,759
of 29,153 outputs
Altmetric has tracked 24,099,692 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,020,419 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 88% 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 357,905 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 72% of its contemporaries.
We're also able to compare this research output to 29,153 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.