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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Evaluation of syndromic algorithms for detecting patients with potentially transmissible infectious diseases based on computerised emergency-department data
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, September 2013
|
| DOI | 10.1186/1472-6947-13-101 |
| Pubmed ID | |
| Authors |
Solweig Gerbier-Colomban, Quentin Gicquel, Anne-Laure Millet, Christophe Riou, Jacqueline Grando, Stefan Darmoni, Véronique Potinet-Pagliaroli, Marie-Hélène Metzger |
| Abstract |
The objective of this study was to ascertain the performance of syndromic algorithms for the early detection of patients in healthcare facilities who have potentially transmissible infectious diseases, using computerised emergency department (ED) data. |
X Demographics
The data shown below were collected from the profiles of 4 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 | 50% |
| India | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 2 | 5% |
| Cameroon | 1 | 2% |
| Spain | 1 | 2% |
| Unknown | 38 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 29% |
| Student > Master | 5 | 12% |
| Student > Bachelor | 5 | 12% |
| Researcher | 5 | 12% |
| Student > Doctoral Student | 4 | 10% |
| Other | 7 | 17% |
| Unknown | 4 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 15 | 36% |
| Nursing and Health Professions | 6 | 14% |
| Computer Science | 4 | 10% |
| Agricultural and Biological Sciences | 3 | 7% |
| Engineering | 3 | 7% |
| Other | 4 | 10% |
| Unknown | 7 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 09 September 2013.
All research outputs
#13,390,169
of 22,719,618 outputs
Outputs from BMC Medical Informatics and Decision Making
#981
of 1,982 outputs
Outputs of similar age
#103,173
of 196,897 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#21
of 46 outputs
Altmetric has tracked 22,719,618 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,982 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 47th percentile – i.e., 47% 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 196,897 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 46 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.