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VGG-TSwinformer: Transformer-based deep learning model for early Alzheimer’s disease prediction

Overview of attention for article published in Computer Methods & Programs in Biomedicine, November 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 (77th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
61 Dimensions

Readers on

mendeley
50 Mendeley
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Title
VGG-TSwinformer: Transformer-based deep learning model for early Alzheimer’s disease prediction
Published in
Computer Methods & Programs in Biomedicine, November 2022
DOI 10.1016/j.cmpb.2022.107291
Pubmed ID
Authors

Zhentao Hu, Zheng Wang, Yong Jin, Wei Hou

Timeline

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 10%
Unspecified 4 8%
Lecturer 3 6%
Student > Master 3 6%
Other 2 4%
Other 3 6%
Unknown 30 60%
Readers by discipline Count As %
Computer Science 9 18%
Unspecified 4 8%
Biochemistry, Genetics and Molecular Biology 1 2%
Chemical Engineering 1 2%
Physics and Astronomy 1 2%
Other 1 2%
Unknown 33 66%
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 16 December 2022.
All research outputs
#5,039,521
of 26,179,695 outputs
Outputs from Computer Methods & Programs in Biomedicine
#203
of 2,115 outputs
Outputs of similar age
#104,340
of 498,422 outputs
Outputs of similar age from Computer Methods & Programs in Biomedicine
#6
of 50 outputs
Altmetric has tracked 26,179,695 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,115 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done well, scoring higher than 88% 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 498,422 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 77% of its contemporaries.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.