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Using data-driven sublanguage pattern mining to induce knowledge models: application in medical image reports knowledge representation

Overview of attention for article published in BMC Medical Informatics and Decision Making, July 2018
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Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
30 Mendeley
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Title
Using data-driven sublanguage pattern mining to induce knowledge models: application in medical image reports knowledge representation
Published in
BMC Medical Informatics and Decision Making, July 2018
DOI 10.1186/s12911-018-0645-3
Pubmed ID
Authors

Yiqing Zhao, Nooshin J. Fesharaki, Hongfang Liu, Jake Luo

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 23%
Student > Master 6 20%
Other 2 7%
Researcher 2 7%
Professor > Associate Professor 2 7%
Other 6 20%
Unknown 5 17%
Readers by discipline Count As %
Computer Science 8 27%
Medicine and Dentistry 7 23%
Nursing and Health Professions 2 7%
Business, Management and Accounting 2 7%
Decision Sciences 1 3%
Other 3 10%
Unknown 7 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 08 July 2018.
All research outputs
#12,218,050
of 13,801,769 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,185
of 1,241 outputs
Outputs of similar age
#165,258
of 199,531 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#85
of 102 outputs
Altmetric has tracked 13,801,769 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,241 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 1st percentile – i.e., 1% 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 199,531 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 102 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.