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Using image mapping towards biomedical and biological data sharing

Overview of attention for article published in Giga Science, September 2013
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (55th percentile)

Mentioned by

twitter
2 tweeters
peer_reviews
1 peer review site
facebook
1 Facebook page

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
20 Mendeley
citeulike
1 CiteULike

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Title
Using image mapping towards biomedical and biological data sharing
Published in
Giga Science, September 2013
DOI 10.1186/2047-217x-2-12
Pubmed ID
24059352
Authors

Nurzi Juana Mohd Zaizi, Dayang Nurfatimah Awang Iskandar

Abstract

: Image-based data integration in eHealth and life sciences is typically concerned with the method used for anatomical space mapping, needed to retrieve, compare and analyse large volumes of biomedical data. In mapping one image onto another image, a mechanism is used to match and find the corresponding spatial regions which have the same meaning between the source and the matching image. Image-based data integration is useful for integrating data of various information structures. Here we discuss a broad range of issues related to data integration of various information structures, review exemplary work on image representation and mapping, and discuss the challenges that these techniques may bring.

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Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters 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 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Hong Kong 2 10%
Unknown 18 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 30%
Other 4 20%
Student > Ph. D. Student 4 20%
Lecturer 1 5%
Lecturer > Senior Lecturer 1 5%
Other 3 15%
Unknown 1 5%
Readers by discipline Count As %
Computer Science 5 25%
Agricultural and Biological Sciences 4 20%
Medicine and Dentistry 2 10%
Linguistics 1 5%
Psychology 1 5%
Other 3 15%
Unknown 4 20%

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 24 September 2013.
All research outputs
#8,530,850
of 15,799,426 outputs
Outputs from Giga Science
#713
of 763 outputs
Outputs of similar age
#74,821
of 169,157 outputs
Outputs of similar age from Giga Science
#1
of 1 outputs
Altmetric has tracked 15,799,426 research outputs across all sources so far. This one is in the 45th percentile – i.e., 45% of other outputs scored the same or lower than it.
So far Altmetric has tracked 763 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.0. 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 169,157 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
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

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