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Automatic lesion detection and segmentation in 18F-flutemetamol positron emission tomography images using deep learning

Overview of attention for article published in BioMedical Engineering OnLine, December 2022
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

news
1 news outlet

Readers on

mendeley
5 Mendeley
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Title
Automatic lesion detection and segmentation in 18F-flutemetamol positron emission tomography images using deep learning
Published in
BioMedical Engineering OnLine, December 2022
DOI 10.1186/s12938-022-01058-8
Pubmed ID
Authors

Chan Ju Ryu

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 20%
Other 1 20%
Student > Master 1 20%
Unknown 2 40%
Readers by discipline Count As %
Nursing and Health Professions 1 20%
Computer Science 1 20%
Medicine and Dentistry 1 20%
Unknown 2 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 23 December 2022.
All research outputs
#4,313,849
of 23,402,852 outputs
Outputs from BioMedical Engineering OnLine
#100
of 834 outputs
Outputs of similar age
#84,742
of 433,968 outputs
Outputs of similar age from BioMedical Engineering OnLine
#1
of 7 outputs
Altmetric has tracked 23,402,852 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 834 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 85% 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 433,968 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 79% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them