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Towards quantifying psychiatric diagnosis using machine learning algorithms and big fMRI data

Overview of attention for article published in Big Data Analytics, May 2018
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)

Mentioned by

twitter
7 X users

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
24 Mendeley
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Title
Towards quantifying psychiatric diagnosis using machine learning algorithms and big fMRI data
Published in
Big Data Analytics, May 2018
DOI 10.1186/s41044-018-0033-0
Authors

Fahad Saeed

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users 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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 21%
Student > Ph. D. Student 4 17%
Researcher 3 13%
Lecturer 1 4%
Professor 1 4%
Other 3 13%
Unknown 7 29%
Readers by discipline Count As %
Computer Science 5 21%
Psychology 4 17%
Engineering 3 13%
Physics and Astronomy 1 4%
Business, Management and Accounting 1 4%
Other 2 8%
Unknown 8 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 16 October 2018.
All research outputs
#6,996,597
of 23,085,832 outputs
Outputs from Big Data Analytics
#10
of 32 outputs
Outputs of similar age
#121,437
of 331,175 outputs
Outputs of similar age from Big Data Analytics
#2
of 4 outputs
Altmetric has tracked 23,085,832 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 32 research outputs from this source. They receive a mean Attention Score of 3.6. This one scored the same or higher as 22 of them.
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 331,175 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 63% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.