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Multimodal Deep Learning Models for Detecting Dementia From Speech and Transcripts

Overview of attention for article published in Frontiers in Aging Neuroscience, March 2022
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
24 Mendeley
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Title
Multimodal Deep Learning Models for Detecting Dementia From Speech and Transcripts
Published in
Frontiers in Aging Neuroscience, March 2022
DOI 10.3389/fnagi.2022.830943
Pubmed ID
Authors

Loukas Ilias, Dimitris Askounis

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 13%
Lecturer > Senior Lecturer 2 8%
Student > Ph. D. Student 2 8%
Student > Master 2 8%
Student > Doctoral Student 1 4%
Other 2 8%
Unknown 12 50%
Readers by discipline Count As %
Computer Science 7 29%
Engineering 3 13%
Nursing and Health Professions 1 4%
Neuroscience 1 4%
Arts and Humanities 1 4%
Other 0 0%
Unknown 11 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 08 April 2022.
All research outputs
#4,338,924
of 23,506,079 outputs
Outputs from Frontiers in Aging Neuroscience
#2,088
of 4,946 outputs
Outputs of similar age
#105,348
of 471,644 outputs
Outputs of similar age from Frontiers in Aging Neuroscience
#117
of 330 outputs
Altmetric has tracked 23,506,079 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,946 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.4. This one has gotten more attention than average, scoring higher than 53% 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 471,644 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 76% of its contemporaries.
We're also able to compare this research output to 330 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 56% of its contemporaries.