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Strategies to improve deep learning-based salivary gland segmentation

Overview of attention for article published in Radiation Oncology, December 2020
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Mentioned by

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1 X user

Citations

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6 Dimensions

Readers on

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25 Mendeley
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Title
Strategies to improve deep learning-based salivary gland segmentation
Published in
Radiation Oncology, December 2020
DOI 10.1186/s13014-020-01721-1
Pubmed ID
Authors

Ward van Rooij, Max Dahele, Hanne Nijhuis, Berend J. Slotman, Wilko F. Verbakel

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 16%
Student > Ph. D. Student 4 16%
Other 1 4%
Lecturer 1 4%
Student > Bachelor 1 4%
Other 2 8%
Unknown 12 48%
Readers by discipline Count As %
Physics and Astronomy 3 12%
Engineering 3 12%
Medicine and Dentistry 2 8%
Agricultural and Biological Sciences 1 4%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Other 2 8%
Unknown 13 52%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 03 December 2020.
All research outputs
#20,672,155
of 23,267,128 outputs
Outputs from Radiation Oncology
#1,702
of 2,090 outputs
Outputs of similar age
#433,438
of 509,341 outputs
Outputs of similar age from Radiation Oncology
#24
of 34 outputs
Altmetric has tracked 23,267,128 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,090 research outputs from this source. They receive a mean Attention Score of 2.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 509,341 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.