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Estimating heterogeneous treatment effect by balancing heterogeneity and fitness

Overview of attention for article published in BMC Bioinformatics, December 2018
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1 X user

Citations

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3 Dimensions

Readers on

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25 Mendeley
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Title
Estimating heterogeneous treatment effect by balancing heterogeneity and fitness
Published in
BMC Bioinformatics, December 2018
DOI 10.1186/s12859-018-2521-7
Pubmed ID
Authors

Weijia Zhang, Thuc Duy Le, Lin Liu, Jiuyong Li

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 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 36%
Lecturer > Senior Lecturer 3 12%
Other 2 8%
Student > Bachelor 2 8%
Student > Master 2 8%
Other 2 8%
Unknown 5 20%
Readers by discipline Count As %
Computer Science 4 16%
Economics, Econometrics and Finance 3 12%
Biochemistry, Genetics and Molecular Biology 2 8%
Medicine and Dentistry 2 8%
Agricultural and Biological Sciences 1 4%
Other 4 16%
Unknown 9 36%
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 22 March 2019.
All research outputs
#20,569,780
of 23,146,350 outputs
Outputs from BMC Bioinformatics
#6,914
of 7,339 outputs
Outputs of similar age
#371,638
of 437,386 outputs
Outputs of similar age from BMC Bioinformatics
#196
of 216 outputs
Altmetric has tracked 23,146,350 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,339 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 1st percentile – i.e., 1% 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 437,386 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 216 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.