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Image-based quantitative analysis of tear film lipid layer thickness for meibomian gland evaluation

Overview of attention for article published in BioMedical Engineering OnLine, November 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

patent
1 patent

Readers on

mendeley
44 Mendeley
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Title
Image-based quantitative analysis of tear film lipid layer thickness for meibomian gland evaluation
Published in
BioMedical Engineering OnLine, November 2017
DOI 10.1186/s12938-017-0426-8
Pubmed ID
Authors

Hyeonha Hwang, Hee-Jae Jeon, Kin Choong Yow, Ho Sik Hwang, EuiHeon Chung

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 18%
Student > Ph. D. Student 5 11%
Student > Doctoral Student 4 9%
Student > Bachelor 4 9%
Researcher 3 7%
Other 7 16%
Unknown 13 30%
Readers by discipline Count As %
Medicine and Dentistry 11 25%
Agricultural and Biological Sciences 3 7%
Nursing and Health Professions 3 7%
Biochemistry, Genetics and Molecular Biology 2 5%
Computer Science 2 5%
Other 8 18%
Unknown 15 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 19 January 2021.
All research outputs
#7,646,569
of 23,281,392 outputs
Outputs from BioMedical Engineering OnLine
#217
of 834 outputs
Outputs of similar age
#151,087
of 439,656 outputs
Outputs of similar age from BioMedical Engineering OnLine
#2
of 9 outputs
Altmetric has tracked 23,281,392 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 834 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 61% 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 439,656 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 7 of them.