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Deep learning-based electroencephalic diagnosis of tinnitus symptom

Overview of attention for article published in Frontiers in Human Neuroscience, April 2023
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Mentioned by

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1 X user

Citations

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5 Dimensions

Readers on

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8 Mendeley
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Title
Deep learning-based electroencephalic diagnosis of tinnitus symptom
Published in
Frontiers in Human Neuroscience, April 2023
DOI 10.3389/fnhum.2023.1126938
Pubmed ID
Authors

Eul-Seok Hong, Hyun-Seok Kim, Sung Kwang Hong, Dimitrios Pantazis, Byoung-Kyong Min

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.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Other 1 13%
Student > Ph. D. Student 1 13%
Student > Bachelor 1 13%
Lecturer 1 13%
Lecturer > Senior Lecturer 1 13%
Other 0 0%
Unknown 3 38%
Readers by discipline Count As %
Psychology 2 25%
Medicine and Dentistry 1 13%
Engineering 1 13%
Unknown 4 50%
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 27 April 2023.
All research outputs
#20,983,210
of 23,613,071 outputs
Outputs from Frontiers in Human Neuroscience
#6,671
of 7,326 outputs
Outputs of similar age
#161,390
of 207,243 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#33
of 46 outputs
Altmetric has tracked 23,613,071 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 7,326 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. 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 207,243 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 46 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.