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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning
|
|---|---|
| Published in |
Nature Biomedical Engineering, February 2018
|
| DOI | 10.1038/s41551-018-0195-0 |
| Pubmed ID | |
| Authors |
Ryan Poplin, Avinash V. Varadarajan, Katy Blumer, Yun Liu, Michael V. McConnell, Greg S. Corrado, Lily Peng, Dale R. Webster |
X Demographics
The data shown below were collected from the profiles of 2,551 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 States | 496 | 19% |
| Spain | 206 | 8% |
| United Kingdom | 140 | 5% |
| India | 74 | 3% |
| Canada | 64 | 3% |
| France | 60 | 2% |
| Germany | 47 | 2% |
| Turkey | 44 | 2% |
| Mexico | 29 | 1% |
| Other | 406 | 16% |
| Unknown | 985 | 39% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2029 | 80% |
| Scientists | 349 | 14% |
| Practitioners (doctors, other healthcare professionals) | 139 | 5% |
| Science communicators (journalists, bloggers, editors) | 34 | 1% |
Mendeley readers
The data shown below were compiled from readership statistics for 1,484 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1484 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 238 | 16% |
| Student > Ph. D. Student | 219 | 15% |
| Student > Master | 163 | 11% |
| Student > Bachelor | 118 | 8% |
| Student > Doctoral Student | 84 | 6% |
| Other | 265 | 18% |
| Unknown | 397 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 291 | 20% |
| Medicine and Dentistry | 253 | 17% |
| Engineering | 163 | 11% |
| Agricultural and Biological Sciences | 52 | 4% |
| Biochemistry, Genetics and Molecular Biology | 49 | 3% |
| Other | 197 | 13% |
| Unknown | 479 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2390. 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 18 April 2024.
All research outputs
#3,403
of 25,866,425 outputs
Outputs from Nature Biomedical Engineering
#2
of 1,162 outputs
Outputs of similar age
#45
of 346,945 outputs
Outputs of similar age from Nature Biomedical Engineering
#1
of 36 outputs
Altmetric has tracked 25,866,425 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,162 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 80.6. 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 346,945 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 99% of its contemporaries.
We're also able to compare this research output to 36 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 97% of its contemporaries.