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A multi-omics supervised autoencoder for pan-cancer clinical outcome endpoints prediction

Overview of attention for article published in BMC Medical Informatics and Decision Making, July 2020
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Mentioned by

twitter
1 tweeter

Citations

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3 Dimensions

Readers on

mendeley
14 Mendeley
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Title
A multi-omics supervised autoencoder for pan-cancer clinical outcome endpoints prediction
Published in
BMC Medical Informatics and Decision Making, July 2020
DOI 10.1186/s12911-020-1114-3
Pubmed ID
Authors

Kaiwen Tan, Weixian Huang, Jinlong Hu, Shoubin Dong

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 29%
Student > Master 3 21%
Other 1 7%
Student > Bachelor 1 7%
Lecturer 1 7%
Other 2 14%
Unknown 2 14%
Readers by discipline Count As %
Computer Science 3 21%
Biochemistry, Genetics and Molecular Biology 2 14%
Medicine and Dentistry 2 14%
Engineering 2 14%
Agricultural and Biological Sciences 1 7%
Other 2 14%
Unknown 2 14%

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 15 August 2020.
All research outputs
#16,514,880
of 18,666,194 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,557
of 1,683 outputs
Outputs of similar age
#258,548
of 306,062 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#9
of 12 outputs
Altmetric has tracked 18,666,194 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 1,683 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. 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 306,062 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 12 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.