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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using machine learning to predict subsequent events after EMS non-conveyance decisions
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, June 2022
|
| DOI | 10.1186/s12911-022-01901-x |
| Pubmed ID | |
| Authors |
Jani Paulin, Akseli Reunamo, Jouni Kurola, Hans Moen, Sanna Salanterä, Heikki Riihimäki, Tero Vesanen, Mari Koivisto, Timo Iirola |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Finland | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 14% |
| Student > Ph. D. Student | 3 | 11% |
| Librarian | 2 | 7% |
| Lecturer | 1 | 4% |
| Unspecified | 1 | 4% |
| Other | 2 | 7% |
| Unknown | 15 | 54% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 3 | 11% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 7% |
| Social Sciences | 2 | 7% |
| Biochemistry, Genetics and Molecular Biology | 1 | 4% |
| Computer Science | 1 | 4% |
| Other | 3 | 11% |
| Unknown | 16 | 57% |
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 27 June 2022.
All research outputs
#13,409,581
of 22,757,090 outputs
Outputs from BMC Medical Informatics and Decision Making
#983
of 1,985 outputs
Outputs of similar age
#180,927
of 440,090 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#15
of 57 outputs
Altmetric has tracked 22,757,090 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,985 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 47th percentile – i.e., 47% 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 440,090 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 56% of its contemporaries.
We're also able to compare this research output to 57 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 68% of its contemporaries.