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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Combining macula clinical signs and patient characteristics for age-related macular degeneration diagnosis: a machine learning approach
|
|---|---|
| Published in |
BMC Ophthalmology, January 2015
|
| DOI | 10.1186/1471-2415-15-10 |
| Pubmed ID | |
| Authors |
Paolo Fraccaro, Massimo Nicolo, Monica Bonetto, Mauro Giacomini, Peter Weller, Carlo Enrico Traverso, Mattia Prosperi, Dympna OSullivan |
| Abstract |
To investigate machine learning methods, ranging from simpler interpretable techniques to complex (non-linear) "black-box" approaches, for automated diagnosis of Age-related Macular Degeneration (AMD). |
X Demographics
The data shown below were collected from the profiles of 7 X users 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 | 14% |
| United States | 1 | 14% |
| Italy | 1 | 14% |
| Unknown | 4 | 57% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 57% |
| Practitioners (doctors, other healthcare professionals) | 2 | 29% |
| Scientists | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 3% |
| Unknown | 90 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 17% |
| Student > Bachelor | 13 | 14% |
| Student > Ph. D. Student | 11 | 12% |
| Student > Master | 11 | 12% |
| Student > Doctoral Student | 8 | 9% |
| Other | 17 | 18% |
| Unknown | 17 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 26 | 28% |
| Computer Science | 12 | 13% |
| Engineering | 8 | 9% |
| Nursing and Health Professions | 4 | 4% |
| Psychology | 4 | 4% |
| Other | 16 | 17% |
| Unknown | 23 | 25% |
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 17 April 2015.
All research outputs
#2,486,655
of 23,881,329 outputs
Outputs from BMC Ophthalmology
#104
of 2,554 outputs
Outputs of similar age
#36,318
of 357,931 outputs
Outputs of similar age from BMC Ophthalmology
#2
of 26 outputs
Altmetric has tracked 23,881,329 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 2,554 research outputs from this source. They receive a mean Attention Score of 2.7. This one has done particularly well, scoring higher than 97% 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 357,931 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 89% of its contemporaries.
We're also able to compare this research output to 26 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 96% of its contemporaries.