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 |
Machine-learning based prediction of prognostic risk factors in patients with invasive candidiasis infection and bacterial bloodstream infection: a singled centered retrospective study
|
|---|---|
| Published in |
BMC Infectious Diseases, February 2022
|
| DOI | 10.1186/s12879-022-07125-8 |
| Pubmed ID | |
| Authors |
Yaling Li, Yutong Wu, Yali Gao, Xueli Niu, Jingyi Li, Mingsui Tang, Chang Fu, Ruiqun Qi, Bing Song, Hongduo Chen, Xinghua Gao, Ying Yang, Xiuhao Guan |
X Demographics
The data shown below were collected from the profiles of 6 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 | 4 | 67% |
| Unknown | 2 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 71 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 6 | 8% |
| Student > Postgraduate | 6 | 8% |
| Student > Ph. D. Student | 6 | 8% |
| Student > Bachelor | 5 | 7% |
| Researcher | 5 | 7% |
| Other | 11 | 15% |
| Unknown | 32 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 10 | 14% |
| Unspecified | 6 | 8% |
| Biochemistry, Genetics and Molecular Biology | 4 | 6% |
| Computer Science | 3 | 4% |
| Immunology and Microbiology | 2 | 3% |
| Other | 11 | 15% |
| Unknown | 35 | 49% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 14 February 2022.
All research outputs
#13,658,772
of 23,885,338 outputs
Outputs from BMC Infectious Diseases
#3,193
of 8,002 outputs
Outputs of similar age
#209,416
of 514,694 outputs
Outputs of similar age from BMC Infectious Diseases
#78
of 237 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,002 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 gotten more attention than average, scoring higher than 58% 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 514,694 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 58% of its contemporaries.
We're also able to compare this research output to 237 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 65% of its contemporaries.