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Filtering data from the collaborative initial glaucoma treatment study for improved identification of glaucoma progression

Overview of attention for article published in BMC Medical Informatics and Decision Making, December 2013
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Title
Filtering data from the collaborative initial glaucoma treatment study for improved identification of glaucoma progression
Published in
BMC Medical Informatics and Decision Making, December 2013
DOI 10.1186/1472-6947-13-137
Pubmed ID
Authors

Greggory J Schell, Mariel S Lavieri, Joshua D Stein, David C Musch

Abstract

Open-angle glaucoma (OAG) is a prevalent, degenerate ocular disease which can lead to blindness without proper clinical management. The tests used to assess disease progression are susceptible to process and measurement noise. The aim of this study was to develop a methodology which accounts for the inherent noise in the data and improve significant disease progression identification.

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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 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Other 3 14%
Student > Postgraduate 3 14%
Student > Bachelor 2 10%
Professor 2 10%
Student > Ph. D. Student 1 5%
Other 3 14%
Unknown 7 33%
Readers by discipline Count As %
Medicine and Dentistry 6 29%
Social Sciences 2 10%
Computer Science 1 5%
Economics, Econometrics and Finance 1 5%
Decision Sciences 1 5%
Other 2 10%
Unknown 8 38%
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 20 January 2014.
All research outputs
#15,289,831
of 22,738,543 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,308
of 1,985 outputs
Outputs of similar age
#191,343
of 306,115 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#33
of 44 outputs
Altmetric has tracked 22,738,543 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,985 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 24th percentile – i.e., 24% 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 306,115 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.