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Clinical risk prediction with random forests for survival, longitudinal, and multivariate (RF-SLAM) data analysis

Overview of attention for article published in BMC Medical Research Methodology, December 2019
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

news
6 news outlets

Citations

dimensions_citation
97 Dimensions

Readers on

mendeley
183 Mendeley
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Title
Clinical risk prediction with random forests for survival, longitudinal, and multivariate (RF-SLAM) data analysis
Published in
BMC Medical Research Methodology, December 2019
DOI 10.1186/s12874-019-0863-0
Pubmed ID
Authors

Shannon Wongvibulsin, Katherine C. Wu, Scott L. Zeger

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 183 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 183 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 16%
Student > Master 24 13%
Researcher 20 11%
Student > Bachelor 16 9%
Student > Doctoral Student 15 8%
Other 18 10%
Unknown 60 33%
Readers by discipline Count As %
Computer Science 29 16%
Medicine and Dentistry 25 14%
Engineering 10 5%
Biochemistry, Genetics and Molecular Biology 8 4%
Mathematics 8 4%
Other 35 19%
Unknown 68 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 42. 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 03 May 2021.
All research outputs
#850,446
of 23,287,285 outputs
Outputs from BMC Medical Research Methodology
#81
of 2,056 outputs
Outputs of similar age
#22,086
of 457,379 outputs
Outputs of similar age from BMC Medical Research Methodology
#5
of 49 outputs
Altmetric has tracked 23,287,285 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,056 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has done particularly well, scoring higher than 96% 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 457,379 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.