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Mining biomedical images towards valuable information retrieval in biomedical and life sciences

Overview of attention for article published in Database: The Journal of Biological Databases & Curation, August 2016
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Article details
Title
Mining biomedical images towards valuable information retrieval in biomedical and life sciences
Published in
Database: The Journal of Biological Databases & Curation, August 2016
DOI 10.1093/database/baw118
Pubmed ID
Authors
Abstract

Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 8 21%
Researcher 8 21%
Student > Bachelor 6 16%
Lecturer 3 8%
Student > Master 3 8%
Other 4 11%
Unknown 6 16%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 16%
Engineering 6 16%
Medicine and Dentistry 5 13%
Agricultural and Biological Sciences 4 11%
Computer Science 4 11%
Other 5 13%
Unknown 8 21%
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 September 2016.
All research outputs
#21,287,262
of 34,363,559 outputs
Outputs from Database: The Journal of Biological Databases & Curation
#583
of 1,191 outputs
Outputs of similar age
#194,973
of 344,135 outputs
Outputs of similar age from Database: The Journal of Biological Databases & Curation
#16
of 26 outputs
Altmetric has tracked 34,363,559 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,191 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has gotten more attention than average, scoring higher than 50% 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 344,135 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.