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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Emergency department triage prediction of clinical outcomes using machine learning models
|
|---|---|
| Published in |
Critical Care, February 2019
|
| DOI | 10.1186/s13054-019-2351-7 |
| Pubmed ID | |
| Authors |
Yoshihiko Raita, Tadahiro Goto, Mohammad Kamal Faridi, David F. M. Brown, Carlos A. Camargo, Kohei Hasegawa |
X Demographics
The data shown below were collected from the profiles of 23 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 3 | 13% |
| United States | 2 | 9% |
| Colombia | 2 | 9% |
| United Kingdom | 2 | 9% |
| Malaysia | 1 | 4% |
| France | 1 | 4% |
| Mexico | 1 | 4% |
| Venezuela, Bolivarian Republic of | 1 | 4% |
| Canada | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 9 | 39% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 16 | 70% |
| Practitioners (doctors, other healthcare professionals) | 4 | 17% |
| Science communicators (journalists, bloggers, editors) | 2 | 9% |
| Scientists | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 492 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 492 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 50 | 10% |
| Student > Ph. D. Student | 37 | 8% |
| Student > Master | 37 | 8% |
| Student > Bachelor | 32 | 7% |
| Other | 27 | 5% |
| Other | 94 | 19% |
| Unknown | 215 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 92 | 19% |
| Computer Science | 38 | 8% |
| Nursing and Health Professions | 35 | 7% |
| Engineering | 29 | 6% |
| Unspecified | 14 | 3% |
| Other | 56 | 11% |
| Unknown | 228 | 46% |
Attention Score in Context
This research output has an Altmetric Attention Score of 22. 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 29 April 2021.
All research outputs
#1,716,440
of 25,385,509 outputs
Outputs from Critical Care
#1,511
of 6,555 outputs
Outputs of similar age
#39,476
of 367,047 outputs
Outputs of similar age from Critical Care
#42
of 110 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,555 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.8. This one has done well, scoring higher than 76% 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 367,047 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 110 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 61% of its contemporaries.