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Variational mode decomposition-based EEG analysis for the classification of disorders of consciousness

Overview of attention for article published in Frontiers in Neuroscience, February 2024
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1 X user

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7 Mendeley
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Title
Variational mode decomposition-based EEG analysis for the classification of disorders of consciousness
Published in
Frontiers in Neuroscience, February 2024
DOI 10.3389/fnins.2024.1340528
Pubmed ID
Authors

Sreelakshmi Raveendran, Raghavendra Kenchaiah, Santhos Kumar, Jayakrushna Sahoo, M. K. Farsana, Ravindranadh Chowdary Mundlamuri, Sonia Bansal, V. S. Binu, A. G. Ramakrishnan, Subasree Ramakrishnan, S. Kala

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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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 29%
Professor 1 14%
Professor > Associate Professor 1 14%
Lecturer 1 14%
Student > Doctoral Student 1 14%
Other 0 0%
Unknown 1 14%
Readers by discipline Count As %
Unspecified 2 29%
Environmental Science 1 14%
Mathematics 1 14%
Neuroscience 1 14%
Engineering 1 14%
Other 0 0%
Unknown 1 14%
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 February 2024.
All research outputs
#22,758,309
of 25,373,627 outputs
Outputs from Frontiers in Neuroscience
#10,135
of 11,538 outputs
Outputs of similar age
#178,686
of 220,056 outputs
Outputs of similar age from Frontiers in Neuroscience
#112
of 135 outputs
Altmetric has tracked 25,373,627 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 11,538 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. 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 220,056 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 135 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.