| 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 |
| Pubmed ID | |
| 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 |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 120 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 16 | 13% |
| Student > Bachelor | 16 | 13% |
| Researcher | 8 | 7% |
| Student > Postgraduate | 8 | 7% |
| Student > Ph. D. Student | 7 | 6% |
| Other | 20 | 17% |
| Unknown | 45 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 30 | 25% |
| Computer Science | 12 | 10% |
| Engineering | 8 | 7% |
| Nursing and Health Professions | 7 | 6% |
| Agricultural and Biological Sciences | 3 | 3% |
| Other | 11 | 9% |
| Unknown | 49 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 28. 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 17 March 2023.
All research outputs
#1,237,926
of 23,549,388 outputs
Outputs from BMC Medical Imaging
#1
of 622 outputs
Outputs of similar age
#28,358
of 345,555 outputs
Outputs of similar age from BMC Medical Imaging
#1
of 10 outputs
Altmetric has tracked 23,549,388 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 622 research outputs from this source. They receive a mean Attention Score of 2.1. This one has done particularly well, scoring higher than 99% 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 345,555 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 10 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