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Quantification of population benefit in evaluation of biomarkers: practical implications for disease detection and prevention

Overview of attention for article published in BMC Medical Informatics and Decision Making, March 2014
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Title
Quantification of population benefit in evaluation of biomarkers: practical implications for disease detection and prevention
Published in
BMC Medical Informatics and Decision Making, March 2014
DOI 10.1186/1472-6947-14-15
Pubmed ID
Authors

Xiaohong Li, Patricia L Blount, Brian J Reid, Thomas L Vaughan

Abstract

With the rapid development of "-omic" technologies, an increasing number of purported biomarkers have been identified for cancer and other diseases. The process of identifying those that are most promising and validating them for use at the population level for prevention and early detection is a critical next step in achieving significant health benefits.

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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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 5%
Unknown 18 95%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 21%
Student > Ph. D. Student 4 21%
Student > Master 3 16%
Professor 2 11%
Other 1 5%
Other 4 21%
Unknown 1 5%
Readers by discipline Count As %
Medicine and Dentistry 5 26%
Agricultural and Biological Sciences 3 16%
Psychology 2 11%
Biochemistry, Genetics and Molecular Biology 2 11%
Mathematics 1 5%
Other 3 16%
Unknown 3 16%
Attention Score in Context

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 10 March 2014.
All research outputs
#18,366,246
of 22,747,498 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,567
of 1,985 outputs
Outputs of similar age
#160,968
of 221,372 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#22
of 28 outputs
Altmetric has tracked 22,747,498 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,985 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 9th percentile – i.e., 9% 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 221,372 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.