You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Interpretable machine learning for predicting 28-day all-cause in-hospital mortality for hypertensive ischemic or hemorrhagic stroke patients in the ICU: a multi-center retrospective cohort study with internal and external cross-validation
|
|---|---|
| Published in |
Frontiers in Neurology, August 2023
|
| DOI | 10.3389/fneur.2023.1185447 |
| Pubmed ID | |
| Authors |
Jian Huang, Huaqiao Chen, Jiewen Deng, Xiaozhu Liu, Tingting Shu, Chengliang Yin, Minjie Duan, Li Fu, Kai Wang, Song Zeng |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 33% |
| Switzerland | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 17% |
| Researcher | 2 | 17% |
| Student > Doctoral Student | 1 | 8% |
| Lecturer | 1 | 8% |
| Other | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 4 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Arts and Humanities | 2 | 17% |
| Unspecified | 1 | 8% |
| Nursing and Health Professions | 1 | 8% |
| Agricultural and Biological Sciences | 1 | 8% |
| Engineering | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 6 | 50% |
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 10 August 2023.
All research outputs
#19,896,022
of 25,321,938 outputs
Outputs from Frontiers in Neurology
#8,208
of 14,418 outputs
Outputs of similar age
#235,835
of 346,952 outputs
Outputs of similar age from Frontiers in Neurology
#215
of 586 outputs
Altmetric has tracked 25,321,938 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,418 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.5. This one is in the 36th percentile – i.e., 36% 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 346,952 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 586 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 56% of its contemporaries.