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Hierarchical multi-class Alzheimer’s disease diagnostic framework using imaging and clinical features

Overview of attention for article published in Frontiers in Aging Neuroscience, August 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 (78th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
7 Mendeley
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Title
Hierarchical multi-class Alzheimer’s disease diagnostic framework using imaging and clinical features
Published in
Frontiers in Aging Neuroscience, August 2022
DOI 10.3389/fnagi.2022.935055
Pubmed ID
Authors

Yao Qin, Jing Cui, Xiaoyan Ge, Yuling Tian, Hongjuan Han, Zhao Fan, Long Liu, Yanhong Luo, Hongmei Yu

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 %
Researcher 1 14%
Lecturer 1 14%
Student > Master 1 14%
Unknown 4 57%
Readers by discipline Count As %
Psychology 2 29%
Chemical Engineering 1 14%
Neuroscience 1 14%
Unknown 3 43%
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 02 September 2022.
All research outputs
#4,272,570
of 23,230,825 outputs
Outputs from Frontiers in Aging Neuroscience
#2,057
of 4,918 outputs
Outputs of similar age
#88,925
of 434,292 outputs
Outputs of similar age from Frontiers in Aging Neuroscience
#153
of 388 outputs
Altmetric has tracked 23,230,825 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 4,918 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.2. This one has gotten more attention than average, scoring higher than 54% 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 434,292 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 78% of its contemporaries.
We're also able to compare this research output to 388 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 54% of its contemporaries.