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Automatic migraine classification via feature selection committee and machine learning techniques over imaging and questionnaire data

Overview of attention for article published in BMC Medical Informatics and Decision Making, April 2017
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1 X user

Citations

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42 Dimensions

Readers on

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90 Mendeley
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Title
Automatic migraine classification via feature selection committee and machine learning techniques over imaging and questionnaire data
Published in
BMC Medical Informatics and Decision Making, April 2017
DOI 10.1186/s12911-017-0434-4
Pubmed ID
Authors

Yolanda Garcia-Chimeno, Begonya Garcia-Zapirain, Marian Gomez-Beldarrain, Begonya Fernandez-Ruanova, Juan Carlos Garcia-Monco

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 1%
Unknown 89 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 15 17%
Researcher 13 14%
Student > Ph. D. Student 10 11%
Student > Doctoral Student 6 7%
Student > Bachelor 5 6%
Other 12 13%
Unknown 29 32%
Readers by discipline Count As %
Computer Science 13 14%
Medicine and Dentistry 13 14%
Neuroscience 12 13%
Engineering 6 7%
Agricultural and Biological Sciences 3 3%
Other 11 12%
Unknown 32 36%
Attention Score in Context

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 04 November 2020.
All research outputs
#20,662,373
of 23,257,423 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,831
of 2,022 outputs
Outputs of similar age
#270,759
of 310,625 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#31
of 33 outputs
Altmetric has tracked 23,257,423 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 2,022 research outputs from this source. They receive a mean Attention Score of 4.9. 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 310,625 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 33 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.