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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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1 tweeter

Citations

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2 Dimensions

Readers on

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14 Mendeley
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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.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 7%
Unknown 13 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 29%
Student > Master 2 14%
Student > Bachelor 2 14%
Professor 2 14%
Lecturer > Senior Lecturer 1 7%
Other 2 14%
Unknown 1 7%
Readers by discipline Count As %
Medicine and Dentistry 5 36%
Agricultural and Biological Sciences 3 21%
Psychology 2 14%
Nursing and Health Professions 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Other 0 0%
Unknown 2 14%

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
#11,149,466
of 14,054,251 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,040
of 1,288 outputs
Outputs of similar age
#128,230
of 188,722 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 1 outputs
Altmetric has tracked 14,054,251 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 1,288 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 5th percentile – i.e., 5% 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 188,722 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them