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Machine learning techniques for personalized breast cancer risk prediction: comparison with the BCRAT and BOADICEA models

Overview of attention for article published in Breast Cancer Research, June 2019
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)

Mentioned by

news
1 news outlet
twitter
5 tweeters

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
87 Mendeley
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Title
Machine learning techniques for personalized breast cancer risk prediction: comparison with the BCRAT and BOADICEA models
Published in
Breast Cancer Research, June 2019
DOI 10.1186/s13058-019-1158-4
Pubmed ID
Authors

Chang Ming, Valeria Viassolo, Nicole Probst-Hensch, Pierre O. Chappuis, Ivo D. Dinov, Maria C. Katapodi

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 87 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 25%
Student > Bachelor 9 10%
Researcher 8 9%
Lecturer 7 8%
Student > Master 7 8%
Other 16 18%
Unknown 18 21%
Readers by discipline Count As %
Computer Science 21 24%
Medicine and Dentistry 11 13%
Nursing and Health Professions 9 10%
Engineering 7 8%
Agricultural and Biological Sciences 3 3%
Other 13 15%
Unknown 23 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 10 September 2020.
All research outputs
#1,723,301
of 16,008,518 outputs
Outputs from Breast Cancer Research
#216
of 1,660 outputs
Outputs of similar age
#43,451
of 267,111 outputs
Outputs of similar age from Breast Cancer Research
#1
of 1 outputs
Altmetric has tracked 16,008,518 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,660 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. 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 267,111 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 1 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