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.
Mendeley readers
Attention Score in Context
Title |
A classification framework for exploiting sparse multi-variate temporal features with application to adverse drug event detection in medical records
|
---|---|
Published in |
BMC Medical Informatics and Decision Making, January 2019
|
DOI | 10.1186/s12911-018-0717-4 |
Pubmed ID | |
Authors |
Francesco Bagattini, Isak Karlsson, Jonathan Rebane, Panagiotis Papapetrou |
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 % |
---|---|---|
Researcher | 15 | 21% |
Student > Master | 8 | 11% |
Student > Ph. D. Student | 7 | 10% |
Other | 6 | 8% |
Student > Doctoral Student | 5 | 7% |
Other | 8 | 11% |
Unknown | 22 | 31% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 15 | 21% |
Medicine and Dentistry | 11 | 15% |
Pharmacology, Toxicology and Pharmaceutical Science | 3 | 4% |
Biochemistry, Genetics and Molecular Biology | 3 | 4% |
Nursing and Health Professions | 3 | 4% |
Other | 11 | 15% |
Unknown | 25 | 35% |
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 21 September 2022.
All research outputs
#14,380,684
of 25,022,483 outputs
Outputs from BMC Medical Informatics and Decision Making
#942
of 2,123 outputs
Outputs of similar age
#216,629
of 449,086 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#24
of 51 outputs
Altmetric has tracked 25,022,483 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,123 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has gotten more attention than average, scoring higher than 53% 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 449,086 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 50% of its contemporaries.
We're also able to compare this research output to 51 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 54% of its contemporaries.