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Comparison of smartphone-based retinal imaging systems for diabetic retinopathy detection using deep learning

Overview of attention for article published in BMC Bioinformatics, July 2020
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1 X user

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110 Mendeley
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Title
Comparison of smartphone-based retinal imaging systems for diabetic retinopathy detection using deep learning
Published in
BMC Bioinformatics, July 2020
DOI 10.1186/s12859-020-03587-2
Pubmed ID
Authors

Mahmut Karakaya, Recep E. Hacisoftaoglu

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 110 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 110 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 15%
Student > Bachelor 11 10%
Researcher 10 9%
Student > Postgraduate 6 5%
Student > Master 5 5%
Other 12 11%
Unknown 49 45%
Readers by discipline Count As %
Medicine and Dentistry 21 19%
Computer Science 14 13%
Engineering 7 6%
Social Sciences 3 3%
Biochemistry, Genetics and Molecular Biology 3 3%
Other 10 9%
Unknown 52 47%
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 11 July 2020.
All research outputs
#20,628,258
of 23,220,133 outputs
Outputs from BMC Bioinformatics
#6,933
of 7,358 outputs
Outputs of similar age
#339,903
of 397,371 outputs
Outputs of similar age from BMC Bioinformatics
#118
of 125 outputs
Altmetric has tracked 23,220,133 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 7,358 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. 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 397,371 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 125 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.