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Application of three statistical models for predicting the risk of diabetes

Overview of attention for article published in BMC Endocrine Disorders, November 2019
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

wikipedia
1 Wikipedia page

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
92 Mendeley
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Title
Application of three statistical models for predicting the risk of diabetes
Published in
BMC Endocrine Disorders, November 2019
DOI 10.1186/s12902-019-0456-2
Pubmed ID
Authors

Siyu Liu, Yue Gao, Yuhang Shen, Min Zhang, Jingjing Li, Pinghui Sun

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 92 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 15%
Student > Bachelor 12 13%
Student > Ph. D. Student 7 8%
Other 5 5%
Researcher 5 5%
Other 14 15%
Unknown 35 38%
Readers by discipline Count As %
Medicine and Dentistry 19 21%
Nursing and Health Professions 8 9%
Computer Science 5 5%
Engineering 4 4%
Biochemistry, Genetics and Molecular Biology 4 4%
Other 11 12%
Unknown 41 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 11 June 2020.
All research outputs
#7,656,056
of 23,308,124 outputs
Outputs from BMC Endocrine Disorders
#248
of 786 outputs
Outputs of similar age
#165,009
of 460,054 outputs
Outputs of similar age from BMC Endocrine Disorders
#10
of 24 outputs
Altmetric has tracked 23,308,124 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 786 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one has gotten more attention than average, scoring higher than 64% 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 460,054 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.