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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A hybrid decision support model to discover informative knowledge in diagnosing acute appendicitis
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, March 2012
|
| DOI | 10.1186/1472-6947-12-17 |
| Pubmed ID | |
| Authors |
Chang Sik Son, Byoung Kuk Jang, Suk Tae Seo, Min Soo Kim, Yoon Nyun Kim |
| Abstract |
The aim of this study is to develop a simple and reliable hybrid decision support model by combining statistical analysis and decision tree algorithms to ensure high accuracy of early diagnosis in patients with suspected acute appendicitis and to identify useful decision rules. |
X Demographics
The data shown below were collected from the profiles of 2 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 Kingdom | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Denmark | 1 | 3% |
| Canada | 1 | 3% |
| Unknown | 38 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 6 | 15% |
| Researcher | 5 | 13% |
| Student > Ph. D. Student | 5 | 13% |
| Professor | 4 | 10% |
| Other | 4 | 10% |
| Other | 10 | 25% |
| Unknown | 6 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 35% |
| Computer Science | 4 | 10% |
| Agricultural and Biological Sciences | 2 | 5% |
| Psychology | 2 | 5% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Other | 8 | 20% |
| Unknown | 9 | 23% |
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 22 April 2014.
All research outputs
#14,725,323
of 22,663,969 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,224
of 1,978 outputs
Outputs of similar age
#97,269
of 156,636 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#18
of 29 outputs
Altmetric has tracked 22,663,969 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,978 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 34th percentile – i.e., 34% 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 156,636 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.