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Locating previously unknown patterns in data-mining results: a dual data- and knowledge-mining method

Overview of attention for article published in BMC Medical Informatics and Decision Making, March 2006
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About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

patent
1 patent

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
26 Mendeley
connotea
1 Connotea
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Title
Locating previously unknown patterns in data-mining results: a dual data- and knowledge-mining method
Published in
BMC Medical Informatics and Decision Making, March 2006
DOI 10.1186/1472-6947-6-13
Pubmed ID
Authors

Mir S Siadaty, William A Knaus

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 4%
Mexico 1 4%
United States 1 4%
Unknown 23 88%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 23%
Other 4 15%
Student > Ph. D. Student 4 15%
Researcher 3 12%
Professor 3 12%
Other 3 12%
Unknown 3 12%
Readers by discipline Count As %
Computer Science 8 31%
Agricultural and Biological Sciences 3 12%
Nursing and Health Professions 2 8%
Medicine and Dentistry 2 8%
Engineering 2 8%
Other 4 15%
Unknown 5 19%
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 01 May 2019.
All research outputs
#7,610,424
of 23,204,238 outputs
Outputs from BMC Medical Informatics and Decision Making
#786
of 2,019 outputs
Outputs of similar age
#24,807
of 71,891 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#4
of 8 outputs
Altmetric has tracked 23,204,238 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 2,019 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 58% 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 71,891 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.