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Risk of bias of prognostic models developed using machine learning: a systematic review in oncology

Overview of attention for article published in Diagnostic and Prognostic Research, July 2022
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#5 of 123)
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

twitter
93 X users

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
32 Mendeley
Title
Risk of bias of prognostic models developed using machine learning: a systematic review in oncology
Published in
Diagnostic and Prognostic Research, July 2022
DOI 10.1186/s41512-022-00126-w
Pubmed ID
Authors

Paula Dhiman, Jie Ma, Constanza L. Andaur Navarro, Benjamin Speich, Garrett Bullock, Johanna A. A. Damen, Lotty Hooft, Shona Kirtley, Richard D. Riley, Ben Van Calster, Karel G. M. Moons, Gary S. Collins

X Demographics

X Demographics

The data shown below were collected from the profiles of 93 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 28%
Student > Bachelor 2 6%
Student > Ph. D. Student 2 6%
Student > Postgraduate 2 6%
Professor > Associate Professor 2 6%
Other 4 13%
Unknown 11 34%
Readers by discipline Count As %
Medicine and Dentistry 5 16%
Nursing and Health Professions 3 9%
Computer Science 2 6%
Agricultural and Biological Sciences 1 3%
Biochemistry, Genetics and Molecular Biology 1 3%
Other 8 25%
Unknown 12 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 53. 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 02 July 2023.
All research outputs
#773,801
of 24,932,434 outputs
Outputs from Diagnostic and Prognostic Research
#5
of 123 outputs
Outputs of similar age
#18,417
of 428,089 outputs
Outputs of similar age from Diagnostic and Prognostic Research
#1
of 5 outputs
Altmetric has tracked 24,932,434 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 123 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. 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 428,089 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 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them