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A systematic comparison of deep learning methods for EEG time series analysis

Overview of attention for article published in Frontiers in Neuroinformatics, February 2023
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (59th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

Mentioned by

twitter
2 X users

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
21 Mendeley
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Title
A systematic comparison of deep learning methods for EEG time series analysis
Published in
Frontiers in Neuroinformatics, February 2023
DOI 10.3389/fninf.2023.1067095
Pubmed ID
Authors

Dominik Walther, Johannes Viehweg, Jens Haueisen, Patrick Mäder

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 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 19%
Lecturer > Senior Lecturer 2 10%
Student > Master 2 10%
Researcher 2 10%
Student > Bachelor 2 10%
Other 4 19%
Unknown 5 24%
Readers by discipline Count As %
Engineering 5 24%
Computer Science 4 19%
Agricultural and Biological Sciences 2 10%
Biochemistry, Genetics and Molecular Biology 2 10%
Neuroscience 2 10%
Other 1 5%
Unknown 5 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 27 February 2023.
All research outputs
#13,833,720
of 23,445,423 outputs
Outputs from Frontiers in Neuroinformatics
#450
of 770 outputs
Outputs of similar age
#134,151
of 346,451 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#8
of 19 outputs
Altmetric has tracked 23,445,423 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 770 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one is in the 38th percentile – i.e., 38% 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 346,451 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 59% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.