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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Supporting meningitis diagnosis amongst infants and children through the use of fuzzy cognitive mapping
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, September 2012
|
| DOI | 10.1186/1472-6947-12-98 |
| Pubmed ID | |
| Authors |
Vijay K Mago, Ravinder Mehta, Ryan Woolrych, Elpiniki I Papageorgiou |
| Abstract |
Meningitis is characterized by an inflammation of the meninges, or the membranes surrounding the brain and spinal cord. Early diagnosis and treatment is crucial for a positive outcome, yet identifying meningitis is a complex process involving an array of signs and symptoms and multiple causal factors which require novel solutions to support clinical decision-making. In this work, we explore the potential of fuzzy cognitive map to assist in the modeling of meningitis, as a support tool for physicians in the accurate diagnosis and treatment of the condition. |
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 % |
|---|---|---|
| Italy | 1 | 25% |
| United States | 1 | 25% |
| India | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 2 | 2% |
| United Kingdom | 2 | 2% |
| Iran, Islamic Republic of | 1 | 1% |
| Unknown | 88 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 14% |
| Student > Master | 12 | 13% |
| Student > Bachelor | 10 | 11% |
| Student > Postgraduate | 7 | 8% |
| Student > Doctoral Student | 6 | 6% |
| Other | 21 | 23% |
| Unknown | 24 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 22 | 24% |
| Computer Science | 10 | 11% |
| Social Sciences | 7 | 8% |
| Nursing and Health Professions | 5 | 5% |
| Engineering | 5 | 5% |
| Other | 14 | 15% |
| Unknown | 30 | 32% |
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 07 September 2012.
All research outputs
#13,019,526
of 22,678,224 outputs
Outputs from BMC Medical Informatics and Decision Making
#914
of 1,978 outputs
Outputs of similar age
#90,253
of 169,085 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#27
of 42 outputs
Altmetric has tracked 22,678,224 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% 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 has gotten more attention than average, scoring higher than 52% 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 169,085 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 42 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.