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X Demographics
Mendeley readers
Attention Score in Context
Title |
Is increasing complexity of algorithms the price for higher accuracy? virtual comparison of three algorithms for tertiary level management of chronic cough in people living with HIV in a low-income country
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Published in |
BMC Medical Informatics and Decision Making, January 2012
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DOI | 10.1186/1472-6947-12-2 |
Pubmed ID | |
Authors |
Constance Mukabatsinda, Jasmine Nguyen, Bettina Bisig, Lutgarde Lynen, Yerma D Coppens, Anita Asiimwe, Jef Van den Ende |
Abstract |
The algorithmic approach to guidelines has been introduced and promoted on a large scale since the 1970s. This study aims at comparing the performance of three algorithms for the management of chronic cough in patients with HIV infection, and at reassessing the current position of algorithmic guidelines in clinical decision making through an analysis of accuracy, harm and complexity. |
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 States | 2 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 2% |
Ecuador | 1 | 2% |
Australia | 1 | 2% |
Brazil | 1 | 2% |
Unknown | 62 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 16 | 24% |
Researcher | 11 | 17% |
Student > Ph. D. Student | 7 | 11% |
Student > Postgraduate | 6 | 9% |
Other | 5 | 8% |
Other | 11 | 17% |
Unknown | 10 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 27 | 41% |
Social Sciences | 10 | 15% |
Nursing and Health Professions | 6 | 9% |
Agricultural and Biological Sciences | 4 | 6% |
Business, Management and Accounting | 2 | 3% |
Other | 2 | 3% |
Unknown | 15 | 23% |
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 13 February 2012.
All research outputs
#17,655,049
of 22,662,201 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,493
of 1,978 outputs
Outputs of similar age
#191,202
of 245,769 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#11
of 15 outputs
Altmetric has tracked 22,662,201 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% 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 21st percentile – i.e., 21% 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 245,769 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% 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 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.