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Building interpretable fuzzy models for high dimensional data analysis in cancer diagnosis

Overview of attention for article published in BMC Genomics, July 2011
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
24 Dimensions

Readers on

mendeley
46 Mendeley
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Title
Building interpretable fuzzy models for high dimensional data analysis in cancer diagnosis
Published in
BMC Genomics, July 2011
DOI 10.1186/1471-2164-12-s2-s5
Pubmed ID
Authors

Zhenyu Wang, Vasile Palade

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 17%
Student > Doctoral Student 5 11%
Other 4 9%
Researcher 4 9%
Student > Master 4 9%
Other 9 20%
Unknown 12 26%
Readers by discipline Count As %
Computer Science 10 22%
Medicine and Dentistry 7 15%
Agricultural and Biological Sciences 6 13%
Engineering 4 9%
Unspecified 1 2%
Other 2 4%
Unknown 16 35%
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 02 August 2023.
All research outputs
#8,534,528
of 25,371,288 outputs
Outputs from BMC Genomics
#3,907
of 11,244 outputs
Outputs of similar age
#47,030
of 130,874 outputs
Outputs of similar age from BMC Genomics
#28
of 88 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. 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 130,874 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 88 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.