| Title |
Use of machine learning to analyse routinely collected intensive care unit data: a systematic review
|
|---|---|
| Published in |
Critical Care, August 2019
|
| DOI | 10.1186/s13054-019-2564-9 |
| Pubmed ID | |
| Authors |
Duncan Shillan, Jonathan A. C. Sterne, Alan Champneys, Ben Gibbison |
X Demographics
The data shown below were collected from the profiles of 66 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 | 17 | 26% |
| France | 4 | 6% |
| Spain | 3 | 5% |
| United States | 3 | 5% |
| Canada | 3 | 5% |
| Switzerland | 2 | 3% |
| Finland | 1 | 2% |
| Belgium | 1 | 2% |
| India | 1 | 2% |
| Other | 10 | 15% |
| Unknown | 21 | 32% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 37 | 56% |
| Scientists | 18 | 27% |
| Practitioners (doctors, other healthcare professionals) | 7 | 11% |
| Science communicators (journalists, bloggers, editors) | 4 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 283 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 283 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 39 | 14% |
| Student > Ph. D. Student | 37 | 13% |
| Student > Master | 26 | 9% |
| Student > Bachelor | 23 | 8% |
| Other | 22 | 8% |
| Other | 52 | 18% |
| Unknown | 84 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 67 | 24% |
| Computer Science | 35 | 12% |
| Engineering | 17 | 6% |
| Nursing and Health Professions | 8 | 3% |
| Agricultural and Biological Sciences | 7 | 2% |
| Other | 50 | 18% |
| Unknown | 99 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 39. 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 11 December 2023.
All research outputs
#1,048,894
of 25,551,063 outputs
Outputs from Critical Care
#822
of 6,583 outputs
Outputs of similar age
#21,940
of 352,357 outputs
Outputs of similar age from Critical Care
#17
of 70 outputs
Altmetric has tracked 25,551,063 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,583 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 87% 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 352,357 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 93% of its contemporaries.
We're also able to compare this research output to 70 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.