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Automatic differentiation of Glaucoma visual field from non-glaucoma visual filed using deep convolutional neural network

Overview of attention for article published in BMC Medical Imaging, October 2018
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Mentioned by

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1 tweeter

Citations

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7 Dimensions

Readers on

mendeley
15 Mendeley
Title
Automatic differentiation of Glaucoma visual field from non-glaucoma visual filed using deep convolutional neural network
Published in
BMC Medical Imaging, October 2018
DOI 10.1186/s12880-018-0273-5
Authors

Fei Li, Zhe Wang, Guoxiang Qu, Diping Song, Ye Yuan, Yang Xu, Kai Gao, Guangwei Luo, Zegu Xiao, Dennis S. C. Lam, Hua Zhong, Yu Qiao, Xiulan Zhang

Twitter Demographics

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

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 %
Unspecified 5 33%
Student > Bachelor 2 13%
Researcher 2 13%
Professor > Associate Professor 2 13%
Student > Ph. D. Student 1 7%
Other 3 20%
Readers by discipline Count As %
Unspecified 6 40%
Medicine and Dentistry 3 20%
Computer Science 3 20%
Biochemistry, Genetics and Molecular Biology 1 7%
Veterinary Science and Veterinary Medicine 1 7%
Other 1 7%

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 06 October 2018.
All research outputs
#11,344,802
of 12,755,705 outputs
Outputs from BMC Medical Imaging
#237
of 285 outputs
Outputs of similar age
#224,681
of 260,078 outputs
Outputs of similar age from BMC Medical Imaging
#1
of 1 outputs
Altmetric has tracked 12,755,705 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 285 research outputs from this source. They receive a mean Attention Score of 2.0. 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 260,078 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 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them