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Use of machine learning techniques in the development and refinement of a predictive model for early diagnosis of ankylosing spondylitis

Overview of attention for article published in Clinical Rheumatology, May 2019
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Mentioned by

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1 X user

Citations

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29 Dimensions

Readers on

mendeley
42 Mendeley
Title
Use of machine learning techniques in the development and refinement of a predictive model for early diagnosis of ankylosing spondylitis
Published in
Clinical Rheumatology, May 2019
DOI 10.1007/s10067-019-04553-x
Pubmed ID
Authors

Atul Deodhar, Martin Rozycki, Cody Garges, Oodaye Shukla, Theresa Arndt, Tara Grabowsky, Yujin Park

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 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 24%
Student > Master 4 10%
Student > Ph. D. Student 4 10%
Lecturer 3 7%
Student > Bachelor 3 7%
Other 2 5%
Unknown 16 38%
Readers by discipline Count As %
Medicine and Dentistry 10 24%
Computer Science 4 10%
Physics and Astronomy 2 5%
Mathematics 1 2%
Agricultural and Biological Sciences 1 2%
Other 4 10%
Unknown 20 48%
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 19 May 2023.
All research outputs
#22,242,003
of 24,820,264 outputs
Outputs from Clinical Rheumatology
#2,852
of 3,245 outputs
Outputs of similar age
#307,927
of 356,218 outputs
Outputs of similar age from Clinical Rheumatology
#67
of 74 outputs
Altmetric has tracked 24,820,264 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 3,245 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. 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 356,218 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 74 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.