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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A Machine Learning Model for Accurate Prediction of Sepsis in ICU Patients
|
|---|---|
| Published in |
Frontiers in Public Health, October 2021
|
| DOI | 10.3389/fpubh.2021.754348 |
| Pubmed ID | |
| Authors |
Dong Wang, Jinbo Li, Yali Sun, Xianfei Ding, Xiaojuan Zhang, Shaohua Liu, Bing Han, Haixu Wang, Xiaoguang Duan, Tongwen Sun |
X Demographics
The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Nigeria | 1 | 8% |
| United States | 1 | 8% |
| United Kingdom | 1 | 8% |
| Unknown | 9 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 92% |
| Practitioners (doctors, other healthcare professionals) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 87 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 11 | 13% |
| Student > Ph. D. Student | 7 | 8% |
| Professor > Associate Professor | 5 | 6% |
| Researcher | 4 | 5% |
| Student > Master | 4 | 5% |
| Other | 4 | 5% |
| Unknown | 52 | 60% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 9% |
| Computer Science | 7 | 8% |
| Nursing and Health Professions | 4 | 5% |
| Biochemistry, Genetics and Molecular Biology | 4 | 5% |
| Business, Management and Accounting | 2 | 2% |
| Other | 10 | 11% |
| Unknown | 52 | 60% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 21 October 2021.
All research outputs
#6,865,633
of 24,878,531 outputs
Outputs from Frontiers in Public Health
#2,590
of 13,221 outputs
Outputs of similar age
#130,090
of 429,537 outputs
Outputs of similar age from Frontiers in Public Health
#131
of 596 outputs
Altmetric has tracked 24,878,531 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 13,221 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has done well, scoring higher than 80% 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 429,537 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 596 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.