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Identifying and understanding determinants of high healthcare costs for breast cancer: a quantile regression machine learning approach

Overview of attention for article published in BMC Health Services Research, November 2020
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Mentioned by

twitter
3 tweeters

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
33 Mendeley
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Title
Identifying and understanding determinants of high healthcare costs for breast cancer: a quantile regression machine learning approach
Published in
BMC Health Services Research, November 2020
DOI 10.1186/s12913-020-05936-6
Pubmed ID
Authors

Liangyuan Hu, Lihua Li, Jiayi Ji, Mark Sanderson

Twitter Demographics

The data shown below were collected from the profiles of 3 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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 12%
Student > Doctoral Student 3 9%
Student > Master 3 9%
Student > Postgraduate 3 9%
Student > Ph. D. Student 2 6%
Other 4 12%
Unknown 14 42%
Readers by discipline Count As %
Medicine and Dentistry 6 18%
Computer Science 2 6%
Business, Management and Accounting 2 6%
Agricultural and Biological Sciences 2 6%
Nursing and Health Professions 1 3%
Other 6 18%
Unknown 14 42%

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 23 December 2020.
All research outputs
#15,331,463
of 19,822,123 outputs
Outputs from BMC Health Services Research
#5,445
of 6,617 outputs
Outputs of similar age
#332,485
of 478,781 outputs
Outputs of similar age from BMC Health Services Research
#580
of 713 outputs
Altmetric has tracked 19,822,123 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,617 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one is in the 15th percentile – i.e., 15% 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 478,781 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 713 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.