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Prediction of breast cancer by profiling of urinary RNA metabolites using Support Vector Machine-based feature selection

Overview of attention for article published in BMC Cancer, April 2009
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Mentioned by

patent
1 patent

Citations

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67 Dimensions

Readers on

mendeley
88 Mendeley
citeulike
1 CiteULike
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Title
Prediction of breast cancer by profiling of urinary RNA metabolites using Support Vector Machine-based feature selection
Published in
BMC Cancer, April 2009
DOI 10.1186/1471-2407-9-104
Pubmed ID
Authors

Carsten Henneges, Dino Bullinger, Richard Fux, Natascha Friese, Harald Seeger, Hans Neubauer, Stefan Laufer, Christoph H Gleiter, Matthias Schwab, Andreas Zell, Bernd Kammerer

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 3%
China 1 1%
Portugal 1 1%
Unknown 83 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 30%
Researcher 11 13%
Student > Master 10 11%
Professor > Associate Professor 5 6%
Professor 4 5%
Other 14 16%
Unknown 18 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 17%
Computer Science 13 15%
Medicine and Dentistry 10 11%
Chemistry 10 11%
Biochemistry, Genetics and Molecular Biology 7 8%
Other 12 14%
Unknown 21 24%
Attention Score in Context

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 22 September 2011.
All research outputs
#7,552,525
of 23,039,416 outputs
Outputs from BMC Cancer
#2,097
of 8,365 outputs
Outputs of similar age
#33,193
of 93,855 outputs
Outputs of similar age from BMC Cancer
#9
of 29 outputs
Altmetric has tracked 23,039,416 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,365 research outputs from this source. They receive a mean Attention Score of 4.3. This one has gotten more attention than average, scoring higher than 68% 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 93,855 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% 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 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.