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Mendeley readers
Attention Score in Context
Title |
A survey on computer aided diagnosis for ocular diseases
|
---|---|
Published in |
BMC Medical Informatics and Decision Making, August 2014
|
DOI | 10.1186/1472-6947-14-80 |
Pubmed ID | |
Authors |
Zhuo Zhang, Ruchir Srivastava, Huiying Liu, Xiangyu Chen, Lixin Duan, Damon Wing Kee Wong, Chee Keong Kwoh, Tien Yin Wong, Jiang Liu |
Abstract |
Computer Aided Diagnosis (CAD), which can automate the detection process for ocular diseases, has attracted extensive attention from clinicians and researchers alike. It not only alleviates the burden on the clinicians by providing objective opinion with valuable insights, but also offers early detection and easy access for patients. |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
India | 4 | 50% |
United Kingdom | 1 | 13% |
Unknown | 3 | 38% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 6 | 75% |
Practitioners (doctors, other healthcare professionals) | 2 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 164 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Switzerland | 1 | <1% |
Unknown | 163 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 28 | 17% |
Student > Master | 24 | 15% |
Student > Bachelor | 17 | 10% |
Researcher | 16 | 10% |
Student > Doctoral Student | 13 | 8% |
Other | 29 | 18% |
Unknown | 37 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 44 | 27% |
Engineering | 31 | 19% |
Medicine and Dentistry | 22 | 13% |
Agricultural and Biological Sciences | 4 | 2% |
Neuroscience | 3 | 2% |
Other | 11 | 7% |
Unknown | 49 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 09 August 2022.
All research outputs
#2,490,741
of 23,053,169 outputs
Outputs from BMC Medical Informatics and Decision Making
#179
of 2,010 outputs
Outputs of similar age
#27,229
of 237,695 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#3
of 31 outputs
Altmetric has tracked 23,053,169 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,010 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 91% 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 237,695 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.