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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Automatic medical encoding with SNOMED categories
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, October 2008
|
| DOI | 10.1186/1472-6947-8-s1-s6 |
| Pubmed ID | |
| Authors |
Patrick Ruch, Julien Gobeill, Christian Lovis, Antoine Geissbühler |
| Abstract |
In this paper, we describe the design and preliminary evaluation of a new type of tools to speed up the encoding of episodes of care using the SNOMED CT terminology. |
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 101 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 4% |
| Netherlands | 2 | 2% |
| Colombia | 1 | <1% |
| Chile | 1 | <1% |
| Austria | 1 | <1% |
| United Kingdom | 1 | <1% |
| Turkey | 1 | <1% |
| Belgium | 1 | <1% |
| Canada | 1 | <1% |
| Other | 2 | 2% |
| Unknown | 86 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 24 | 24% |
| Researcher | 23 | 23% |
| Student > Master | 15 | 15% |
| Professor > Associate Professor | 8 | 8% |
| Other | 7 | 7% |
| Other | 17 | 17% |
| Unknown | 7 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 45 | 45% |
| Medicine and Dentistry | 20 | 20% |
| Agricultural and Biological Sciences | 14 | 14% |
| Engineering | 7 | 7% |
| Nursing and Health Professions | 2 | 2% |
| Other | 6 | 6% |
| Unknown | 7 | 7% |
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 23 August 2019.
All research outputs
#6,914,371
of 22,675,759 outputs
Outputs from BMC Medical Informatics and Decision Making
#676
of 1,978 outputs
Outputs of similar age
#30,629
of 91,594 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#5
of 15 outputs
Altmetric has tracked 22,675,759 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 1,978 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 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 91,594 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 65% of its contemporaries.
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 has gotten more attention than average, scoring higher than 66% of its contemporaries.