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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using machine learning for the early prediction of sepsis-associated ARDS in the ICU and identification of clinical phenotypes with differential responses to treatment
|
|---|---|
| Published in |
Frontiers in Physiology, December 2022
|
| DOI | 10.3389/fphys.2022.1050849 |
| Pubmed ID | |
| Authors |
Yu Bai, Jingen Xia, Xu Huang, Shengsong Chen, Qingyuan Zhan |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 25 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 16% |
| Student > Bachelor | 2 | 8% |
| Other | 1 | 4% |
| Student > Doctoral Student | 1 | 4% |
| Student > Master | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 15 | 60% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 3 | 12% |
| Veterinary Science and Veterinary Medicine | 1 | 4% |
| Business, Management and Accounting | 1 | 4% |
| Computer Science | 1 | 4% |
| Nursing and Health Professions | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 16 | 64% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 12 December 2022.
All research outputs
#20,723,550
of 23,322,966 outputs
Outputs from Frontiers in Physiology
#9,657
of 14,050 outputs
Outputs of similar age
#344,514
of 436,554 outputs
Outputs of similar age from Frontiers in Physiology
#347
of 588 outputs
Altmetric has tracked 23,322,966 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,050 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 436,554 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 588 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.