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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine learning approach for the prediction of 30-day mortality in patients with sepsis-associated encephalopathy
|
|---|---|
| Published in |
BMC Medical Research Methodology, July 2022
|
| DOI | 10.1186/s12874-022-01664-z |
| Pubmed ID | |
| Authors |
Liwei Peng, Chi Peng, Fan Yang, Jian Wang, Wei Zuo, Chao Cheng, Zilong Mao, Zhichao Jin, Weixin Li |
X Demographics
The data shown below were collected from the profiles of 4 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 | 1 | 25% |
| United Kingdom | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 2 | 9% |
| Student > Doctoral Student | 2 | 9% |
| Student > Ph. D. Student | 2 | 9% |
| Lecturer | 1 | 4% |
| Researcher | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 15 | 65% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 3 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 9% |
| Agricultural and Biological Sciences | 1 | 4% |
| Nursing and Health Professions | 1 | 4% |
| Economics, Econometrics and Finance | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 14 | 61% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 06 July 2022.
All research outputs
#15,660,793
of 23,885,338 outputs
Outputs from BMC Medical Research Methodology
#1,517
of 2,124 outputs
Outputs of similar age
#228,693
of 423,054 outputs
Outputs of similar age from BMC Medical Research Methodology
#33
of 53 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,124 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 25th percentile – i.e., 25% 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 423,054 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 53 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.