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Dynamic models to predict health outcomes: current status and methodological challenges

Overview of attention for article published in Diagnostic and Prognostic Research, December 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#18 of 126)
  • High Attention Score compared to outputs of the same age (91st percentile)

Mentioned by

blogs
1 blog
twitter
24 X users

Citations

dimensions_citation
70 Dimensions

Readers on

mendeley
80 Mendeley
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Title
Dynamic models to predict health outcomes: current status and methodological challenges
Published in
Diagnostic and Prognostic Research, December 2018
DOI 10.1186/s41512-018-0045-2
Pubmed ID
Authors

David A. Jenkins, Matthew Sperrin, Glen P. Martin, Niels Peek

X Demographics

X Demographics

The data shown below were collected from the profiles of 24 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 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 80 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 21%
Student > Ph. D. Student 13 16%
Student > Master 5 6%
Student > Bachelor 4 5%
Other 4 5%
Other 9 11%
Unknown 28 35%
Readers by discipline Count As %
Medicine and Dentistry 14 18%
Nursing and Health Professions 7 9%
Mathematics 5 6%
Computer Science 4 5%
Business, Management and Accounting 2 3%
Other 12 15%
Unknown 36 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 November 2020.
All research outputs
#1,606,974
of 25,559,053 outputs
Outputs from Diagnostic and Prognostic Research
#18
of 126 outputs
Outputs of similar age
#35,893
of 445,027 outputs
Outputs of similar age from Diagnostic and Prognostic Research
#2
of 3 outputs
Altmetric has tracked 25,559,053 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 126 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.3. This one has done well, scoring higher than 86% 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 445,027 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 91% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.