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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Mining FDA drug labels for medical conditions
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, April 2013
|
| DOI | 10.1186/1472-6947-13-53 |
| Pubmed ID | |
| Authors |
Qi Li, Louise Deleger, Todd Lingren, Haijun Zhai, Megan Kaiser, Laura Stoutenborough, Anil G Jegga, Kevin Bretonnel Cohen, Imre Solti |
| Abstract |
Cincinnati Children's Hospital Medical Center (CCHMC) has built the initial Natural Language Processing (NLP) component to extract medications with their corresponding medical conditions (Indications, Contraindications, Overdosage, and Adverse Reactions) as triples of medication-related information ([(1) drug name]-[(2) medical condition]-[(3) LOINC section header]) for an intelligent database system, in order to improve patient safety and the quality of health care. The Food and Drug Administration's (FDA) drug labels are used to demonstrate the feasibility of building the triples as an intelligent database system task. |
X Demographics
The data shown below were collected from the profiles of 5 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 | 2 | 40% |
| India | 2 | 40% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 3 | 60% |
| Scientists | 1 | 20% |
| Members of the public | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 5% |
| Switzerland | 1 | <1% |
| Germany | 1 | <1% |
| Australia | 1 | <1% |
| Netherlands | 1 | <1% |
| Unknown | 110 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 24 | 20% |
| Student > Master | 16 | 13% |
| Student > Ph. D. Student | 13 | 11% |
| Student > Doctoral Student | 11 | 9% |
| Student > Postgraduate | 7 | 6% |
| Other | 23 | 19% |
| Unknown | 26 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 26 | 22% |
| Medicine and Dentistry | 23 | 19% |
| Agricultural and Biological Sciences | 8 | 7% |
| Psychology | 6 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 4% |
| Other | 20 | 17% |
| Unknown | 32 | 27% |
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 23 September 2013.
All research outputs
#13,859,387
of 23,881,329 outputs
Outputs from BMC Medical Informatics and Decision Making
#967
of 2,030 outputs
Outputs of similar age
#103,656
of 196,097 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#18
of 34 outputs
Altmetric has tracked 23,881,329 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 2,030 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 51% 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 196,097 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.