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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Integration of tools for binding archetypes to SNOMED CT
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, October 2008
|
| DOI | 10.1186/1472-6947-8-s1-s7 |
| Pubmed ID | |
| Authors |
Erik Sundvall, Rahil Qamar, Mikael Nyström, Mattias Forss, Håkan Petersson, Daniel Karlsson, Hans Åhlfeldt, Alan Rector |
| Abstract |
The Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems. |
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 % |
|---|---|---|
| India | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 4% |
| Netherlands | 3 | 4% |
| Turkey | 1 | 1% |
| Ireland | 1 | 1% |
| Germany | 1 | 1% |
| Sweden | 1 | 1% |
| Brazil | 1 | 1% |
| Belgium | 1 | 1% |
| Spain | 1 | 1% |
| Other | 0 | 0% |
| Unknown | 61 | 82% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 22% |
| Student > Ph. D. Student | 14 | 19% |
| Student > Master | 14 | 19% |
| Student > Doctoral Student | 5 | 7% |
| Student > Bachelor | 4 | 5% |
| Other | 15 | 20% |
| Unknown | 6 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 40 | 54% |
| Medicine and Dentistry | 10 | 14% |
| Engineering | 6 | 8% |
| Agricultural and Biological Sciences | 3 | 4% |
| Linguistics | 2 | 3% |
| Other | 6 | 8% |
| Unknown | 7 | 9% |
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 21 June 2014.
All research outputs
#18,373,874
of 22,757,541 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,567
of 1,985 outputs
Outputs of similar age
#84,314
of 91,708 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#13
of 15 outputs
Altmetric has tracked 22,757,541 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% 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 9th percentile – i.e., 9% 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 91,708 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.