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Using artificial intelligence reading label system in diabetic retinopathy grading training of junior ophthalmology residents and medical students

Overview of attention for article published in BMC Medical Education, April 2022
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Mentioned by

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2 X users

Citations

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8 Dimensions

Readers on

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15 Mendeley
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Title
Using artificial intelligence reading label system in diabetic retinopathy grading training of junior ophthalmology residents and medical students
Published in
BMC Medical Education, April 2022
DOI 10.1186/s12909-022-03272-3
Pubmed ID
Authors

Ruoan Han, Weihong Yu, Huan Chen, Youxin Chen

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 20%
Other 2 13%
Student > Master 2 13%
Professor 1 7%
Researcher 1 7%
Other 1 7%
Unknown 5 33%
Readers by discipline Count As %
Medicine and Dentistry 4 27%
Biochemistry, Genetics and Molecular Biology 2 13%
Decision Sciences 1 7%
Chemical Engineering 1 7%
Social Sciences 1 7%
Other 1 7%
Unknown 5 33%
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 10 April 2022.
All research outputs
#19,416,201
of 23,885,338 outputs
Outputs from BMC Medical Education
#2,987
of 3,619 outputs
Outputs of similar age
#319,670
of 430,331 outputs
Outputs of similar age from BMC Medical Education
#152
of 189 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,619 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 4th percentile – i.e., 4% 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 430,331 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 189 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.