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Supervised Learning Classifiers for Electrical Impedance-based Bladder State Detection

Overview of attention for article published in Scientific Reports, March 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

twitter
6 X users
patent
2 patents

Citations

dimensions_citation
26 Dimensions

Readers on

mendeley
56 Mendeley
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Title
Supervised Learning Classifiers for Electrical Impedance-based Bladder State Detection
Published in
Scientific Reports, March 2018
DOI 10.1038/s41598-018-23786-5
Pubmed ID
Authors

Eoghan Dunne, Adam Santorelli, Brian McGinley, Geraldine Leader, Martin O’Halloran, Emily Porter

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users 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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 20%
Researcher 5 9%
Student > Master 5 9%
Student > Bachelor 4 7%
Professor 3 5%
Other 9 16%
Unknown 19 34%
Readers by discipline Count As %
Engineering 16 29%
Medicine and Dentistry 4 7%
Computer Science 3 5%
Psychology 2 4%
Agricultural and Biological Sciences 2 4%
Other 7 13%
Unknown 22 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 25 April 2024.
All research outputs
#3,477,813
of 25,947,988 outputs
Outputs from Scientific Reports
#29,788
of 144,104 outputs
Outputs of similar age
#67,218
of 347,165 outputs
Outputs of similar age from Scientific Reports
#758
of 3,508 outputs
Altmetric has tracked 25,947,988 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 144,104 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.8. This one has done well, scoring higher than 79% 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 347,165 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 80% of its contemporaries.
We're also able to compare this research output to 3,508 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.