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Non-invasive and accurate risk evaluation of cerebrovascular disease using retinal fundus photo based on deep learning

Overview of attention for article published in Frontiers in Neurology, September 2023
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1 X user

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10 Mendeley
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Title
Non-invasive and accurate risk evaluation of cerebrovascular disease using retinal fundus photo based on deep learning
Published in
Frontiers in Neurology, September 2023
DOI 10.3389/fneur.2023.1257388
Pubmed ID
Authors

Lin An, Jia Qin, Weili Jiang, Penghao Luo, Xiaoyan Luo, Yuzheng Lai, Mei Jin

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 10%
Researcher 1 10%
Unknown 8 80%
Readers by discipline Count As %
Computer Science 1 10%
Neuroscience 1 10%
Unknown 8 80%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 07 September 2023.
All research outputs
#21,864,816
of 24,396,012 outputs
Outputs from Frontiers in Neurology
#9,956
of 13,442 outputs
Outputs of similar age
#134,677
of 164,930 outputs
Outputs of similar age from Frontiers in Neurology
#172
of 285 outputs
Altmetric has tracked 24,396,012 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,442 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 164,930 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 285 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.