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An investigation of privacy preservation in deep learning-based eye-tracking

Overview of attention for article published in BioMedical Engineering OnLine, September 2022
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users

Readers on

mendeley
15 Mendeley
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Title
An investigation of privacy preservation in deep learning-based eye-tracking
Published in
BioMedical Engineering OnLine, September 2022
DOI 10.1186/s12938-022-01035-1
Pubmed ID
Authors

Salman Seyedi, Zifan Jiang, Allan Levey, Gari D. Clifford

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 13%
Unspecified 1 7%
Student > Doctoral Student 1 7%
Student > Master 1 7%
Unknown 10 67%
Readers by discipline Count As %
Unspecified 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Computer Science 1 7%
Psychology 1 7%
Engineering 1 7%
Other 0 0%
Unknown 10 67%
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 20 September 2022.
All research outputs
#16,960,534
of 24,932,492 outputs
Outputs from BioMedical Engineering OnLine
#450
of 855 outputs
Outputs of similar age
#246,957
of 425,031 outputs
Outputs of similar age from BioMedical Engineering OnLine
#6
of 9 outputs
Altmetric has tracked 24,932,492 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 855 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 33rd percentile – i.e., 33% 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 425,031 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.