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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine learning-based identification and rule-based normalization of adverse drug reactions in drug labels
|
|---|---|
| Published in |
BMC Bioinformatics, December 2019
|
| DOI | 10.1186/s12859-019-3195-5 |
| Pubmed ID | |
| Authors |
Mert Tiftikci, Arzucan Özgür, Yongqun He, Junguk Hur |
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 % |
|---|---|---|
| Spain | 1 | 33% |
| United States | 1 | 33% |
| United Kingdom | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 48 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 6 | 13% |
| Student > Ph. D. Student | 5 | 10% |
| Student > Bachelor | 4 | 8% |
| Student > Doctoral Student | 3 | 6% |
| Professor | 3 | 6% |
| Other | 8 | 17% |
| Unknown | 19 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 19% |
| Medicine and Dentistry | 4 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 8% |
| Agricultural and Biological Sciences | 3 | 6% |
| Engineering | 2 | 4% |
| Other | 10 | 21% |
| Unknown | 16 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 11 October 2022.
All research outputs
#6,831,341
of 23,885,338 outputs
Outputs from BMC Bioinformatics
#2,554
of 7,484 outputs
Outputs of similar age
#144,455
of 463,060 outputs
Outputs of similar age from BMC Bioinformatics
#70
of 218 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 7,484 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 64% 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 463,060 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 68% of its contemporaries.
We're also able to compare this research output to 218 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.