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Deep learning-based feature selection and prediction system for autism spectrum disorder using a hybrid meta-heuristics approach

Overview of attention for article published in Journal of Intelligent & Fuzzy Systems, July 2023
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#7 of 233)
  • High Attention Score compared to outputs of the same age (85th percentile)

Mentioned by

news
1 news outlet

Readers on

mendeley
8 Mendeley
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Title
Deep learning-based feature selection and prediction system for autism spectrum disorder using a hybrid meta-heuristics approach
Published in
Journal of Intelligent & Fuzzy Systems, July 2023
DOI 10.3233/jifs-223694
Authors

K. Chola Raja, S. Kannimuthu

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 %
Unspecified 1 13%
Student > Ph. D. Student 1 13%
Unknown 6 75%
Readers by discipline Count As %
Unspecified 1 13%
Computer Science 1 13%
Unknown 6 75%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 21 March 2023.
All research outputs
#3,166,055
of 24,008,549 outputs
Outputs from Journal of Intelligent & Fuzzy Systems
#7
of 233 outputs
Outputs of similar age
#26,238
of 181,513 outputs
Outputs of similar age from Journal of Intelligent & Fuzzy Systems
#1
of 2 outputs
Altmetric has tracked 24,008,549 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 233 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 96% 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 181,513 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 85% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them