↓ Skip to main content

Deep Learning Provides Exceptional Accuracy to ECoG-Based Functional Language Mapping for Epilepsy Surgery

Overview of attention for article published in Frontiers in Neuroscience, May 2020
Altmetric Badge

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 (84th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

news
1 news outlet
twitter
9 X users

Readers on

mendeley
67 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Deep Learning Provides Exceptional Accuracy to ECoG-Based Functional Language Mapping for Epilepsy Surgery
Published in
Frontiers in Neuroscience, May 2020
DOI 10.3389/fnins.2020.00409
Pubmed ID
Authors

Harish RaviPrakash, Milena Korostenskaja, Eduardo M. Castillo, Ki H. Lee, Christine M. Salinas, James Baumgartner, Syed M. Anwar, Concetto Spampinato, Ulas Bagci

Timeline

Login to access the full chart related to this output.

If you don’t have an account, click here to discover Explorer

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 X users 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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 16%
Student > Ph. D. Student 11 16%
Student > Bachelor 7 10%
Student > Master 6 9%
Student > Postgraduate 5 7%
Other 9 13%
Unknown 18 27%
Readers by discipline Count As %
Neuroscience 13 19%
Medicine and Dentistry 10 15%
Engineering 8 12%
Computer Science 7 10%
Psychology 2 3%
Other 4 6%
Unknown 23 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 18 May 2020.
All research outputs
#2,460,187
of 26,560,265 outputs
Outputs from Frontiers in Neuroscience
#1,435
of 11,939 outputs
Outputs of similar age
#63,466
of 418,872 outputs
Outputs of similar age from Frontiers in Neuroscience
#95
of 382 outputs
Altmetric has tracked 26,560,265 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,939 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.2. This one has done well, scoring higher than 87% 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 418,872 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 84% of its contemporaries.
We're also able to compare this research output to 382 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 74% of its contemporaries.