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DBCSMOTE: a clustering-based oversampling technique for data-imbalanced warfarin dose prediction

Overview of attention for article published in BMC Medical Genomics, October 2020
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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1 X user

Citations

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9 Dimensions

Readers on

mendeley
21 Mendeley
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Title
DBCSMOTE: a clustering-based oversampling technique for data-imbalanced warfarin dose prediction
Published in
BMC Medical Genomics, October 2020
DOI 10.1186/s12920-020-00781-2
Pubmed ID
Authors

Yanyun Tao, Yuzhen Zhang, Bin Jiang

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 24%
Student > Ph. D. Student 5 24%
Other 3 14%
Researcher 2 10%
Unspecified 1 5%
Other 2 10%
Unknown 3 14%
Readers by discipline Count As %
Computer Science 5 24%
Medicine and Dentistry 3 14%
Pharmacology, Toxicology and Pharmaceutical Science 2 10%
Chemical Engineering 1 5%
Nursing and Health Professions 1 5%
Other 3 14%
Unknown 6 29%
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 October 2020.
All research outputs
#15,642,530
of 23,253,955 outputs
Outputs from BMC Medical Genomics
#689
of 1,245 outputs
Outputs of similar age
#258,481
of 419,872 outputs
Outputs of similar age from BMC Medical Genomics
#19
of 43 outputs
Altmetric has tracked 23,253,955 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,245 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 35th percentile – i.e., 35% 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 419,872 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.