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Predicting chemotherapy response using a variational autoencoder approach

Overview of attention for article published in BMC Bioinformatics, September 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (60th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
7 X users

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
36 Mendeley
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Title
Predicting chemotherapy response using a variational autoencoder approach
Published in
BMC Bioinformatics, September 2021
DOI 10.1186/s12859-021-04339-6
Pubmed ID
Authors

Qi Wei, Stephen A. Ramsey

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 14%
Student > Ph. D. Student 5 14%
Student > Master 4 11%
Student > Bachelor 4 11%
Student > Postgraduate 3 8%
Other 3 8%
Unknown 12 33%
Readers by discipline Count As %
Computer Science 8 22%
Biochemistry, Genetics and Molecular Biology 3 8%
Engineering 3 8%
Medicine and Dentistry 3 8%
Immunology and Microbiology 1 3%
Other 3 8%
Unknown 15 42%
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 28 September 2021.
All research outputs
#13,045,234
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#3,691
of 7,388 outputs
Outputs of similar age
#168,234
of 433,316 outputs
Outputs of similar age from BMC Bioinformatics
#80
of 149 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,388 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 48th percentile – i.e., 48% 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 433,316 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 60% of its contemporaries.
We're also able to compare this research output to 149 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.