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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

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3 X users

Citations

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11 Dimensions

Readers on

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51 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

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 5 10%
Researcher 4 8%
Student > Doctoral Student 4 8%
Student > Ph. D. Student 3 6%
Student > Master 3 6%
Other 7 14%
Unknown 25 49%
Readers by discipline Count As %
Medicine and Dentistry 6 12%
Agricultural and Biological Sciences 4 8%
Business, Management and Accounting 2 4%
Computer Science 2 4%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Other 9 18%
Unknown 26 51%
Attention Score in Context

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
#18,108,894
of 23,263,851 outputs
Outputs from BMC Health Services Research
#6,427
of 7,786 outputs
Outputs of similar age
#358,650
of 508,437 outputs
Outputs of similar age from BMC Health Services Research
#134
of 159 outputs
Altmetric has tracked 23,263,851 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 7,786 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. 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 508,437 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 159 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.