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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Predicting the outcome for COVID-19 patients by applying time series classification to electronic health records
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, July 2022
|
| DOI | 10.1186/s12911-022-01931-5 |
| Pubmed ID | |
| Authors |
Davi Silva Rodrigues, Ana Catharina S. Nastri, Marcello M. Magri, Maura Salaroli de Oliveira, Ester C. Sabino, Pedro H. M. F. Figueiredo, Anna S. Levin, Maristela P. Freire, Leila S. Harima, Fátima L. S. Nunes, João Eduardo Ferreira |
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 % |
|---|---|---|
| Unknown | 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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 26 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 12% |
| Student > Master | 3 | 12% |
| Student > Bachelor | 3 | 12% |
| Librarian | 2 | 8% |
| Researcher | 2 | 8% |
| Other | 2 | 8% |
| Unknown | 11 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 19% |
| Engineering | 2 | 8% |
| Nursing and Health Professions | 2 | 8% |
| Environmental Science | 1 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 4% |
| Other | 3 | 12% |
| Unknown | 12 | 46% |
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 17 July 2022.
All research outputs
#15,376,252
of 22,875,477 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,316
of 1,993 outputs
Outputs of similar age
#218,875
of 400,819 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#25
of 53 outputs
Altmetric has tracked 22,875,477 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,993 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 24th percentile – i.e., 24% 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 400,819 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% 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 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.