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DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network

Overview of attention for article published in BMC Medical Research Methodology, February 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
1 news outlet
blogs
2 blogs
twitter
35 X users
patent
1 patent
facebook
3 Facebook pages
reddit
1 Redditor

Citations

dimensions_citation
929 Dimensions

Readers on

mendeley
941 Mendeley
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Title
DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network
Published in
BMC Medical Research Methodology, February 2018
DOI 10.1186/s12874-018-0482-1
Pubmed ID
Authors

Jared L. Katzman, Uri Shaham, Alexander Cloninger, Jonathan Bates, Tingting Jiang, Yuval Kluger

X Demographics

X Demographics

The data shown below were collected from the profiles of 35 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 941 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 941 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 174 18%
Researcher 130 14%
Student > Master 109 12%
Student > Bachelor 57 6%
Student > Doctoral Student 43 5%
Other 123 13%
Unknown 305 32%
Readers by discipline Count As %
Computer Science 224 24%
Medicine and Dentistry 78 8%
Engineering 63 7%
Biochemistry, Genetics and Molecular Biology 55 6%
Mathematics 43 5%
Other 130 14%
Unknown 348 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 43. 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 31 May 2022.
All research outputs
#933,099
of 24,980,180 outputs
Outputs from BMC Medical Research Methodology
#81
of 2,229 outputs
Outputs of similar age
#21,094
of 335,986 outputs
Outputs of similar age from BMC Medical Research Methodology
#2
of 22 outputs
Altmetric has tracked 24,980,180 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,229 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. This one has done particularly well, scoring higher than 96% 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 335,986 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.