The data shown below were collected from the profiles of 48 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Adopting machine learning to automatically identify candidate patients for corneal refractive surgery
|
|---|---|
| Published in |
npj Digital Medicine, June 2019
|
| DOI | 10.1038/s41746-019-0135-8 |
| Pubmed ID | |
| Authors |
Tae Keun Yoo, Ik Hee Ryu, Geunyoung Lee, Youngnam Kim, Jin Kuk Kim, In Sik Lee, Jung Sub Kim, Tyler Hyungtaek Rim |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 17% |
| India | 3 | 6% |
| France | 2 | 4% |
| Canada | 1 | 2% |
| United Kingdom | 1 | 2% |
| Turkey | 1 | 2% |
| Nepal | 1 | 2% |
| Singapore | 1 | 2% |
| Switzerland | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 29 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 33 | 69% |
| Scientists | 12 | 25% |
| Practitioners (doctors, other healthcare professionals) | 2 | 4% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 72 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 15% |
| Unspecified | 7 | 10% |
| Student > Bachelor | 7 | 10% |
| Student > Master | 7 | 10% |
| Student > Ph. D. Student | 7 | 10% |
| Other | 15 | 21% |
| Unknown | 18 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 17 | 24% |
| Unspecified | 8 | 11% |
| Computer Science | 5 | 7% |
| Engineering | 5 | 7% |
| Physics and Astronomy | 3 | 4% |
| Other | 11 | 15% |
| Unknown | 23 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 56. 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 20 November 2023.
All research outputs
#817,639
of 26,567,854 outputs
Outputs from npj Digital Medicine
#259
of 1,147 outputs
Outputs of similar age
#16,963
of 370,823 outputs
Outputs of similar age from npj Digital Medicine
#16
of 37 outputs
Altmetric has tracked 26,567,854 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,147 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 52.0. This one has done well, scoring higher than 77% 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 370,823 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 95% of its contemporaries.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.