↓ Skip to main content

Applications of Machine Learning in Cancer Prediction and Prognosis

Overview of attention for article published in Cancer Informatics, October 2017
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#1 of 474)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
154 X users
patent
47 patents
facebook
1 Facebook page
wikipedia
4 Wikipedia pages
reddit
6 Redditors

Readers on

mendeley
1602 Mendeley
citeulike
2 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Article details
Title
Applications of Machine Learning in Cancer Prediction and Prognosis
Published in
Cancer Informatics, October 2017
DOI 10.1177/117693510600200030
Pubmed ID
Authors

Login to access the Attention Digest and the Sentiment Analysis related to this output.

Timeline Attention over time Attention Score history
Login to access the full charts related to this output.
Activity
Login to access the full charts related to this output.
X Demographics

X Demographics

The data shown below were collected from the profiles of 154 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 1,602 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Login to view Mendeley reader trends over time.

Geographical breakdown

Geographical breakdown
Country Count As %
United States 8 <1%
France 4 <1%
Australia 3 <1%
Germany 3 <1%
India 2 <1%
Israel 2 <1%
United Kingdom 2 <1%
Switzerland 2 <1%
Canada 2 <1%
Other 9 <1%
Unknown 1565 98%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 237 15%
Student > Ph. D. Student 227 14%
Student > Bachelor 173 11%
Researcher 142 9%
Student > Doctoral Student 61 4%
Other 218 14%
Unknown 544 34%
Readers by discipline
Readers by discipline Count As %
Computer Science 329 21%
Engineering 174 11%
Medicine and Dentistry 135 8%
Biochemistry, Genetics and Molecular Biology 93 6%
Agricultural and Biological Sciences 65 4%
Other 211 13%
Unknown 595 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 142. 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 11 August 2026.
All research outputs
#366,804
of 34,350,842 outputs
Outputs from Cancer Informatics
#1
of 474 outputs
Outputs of similar age
#5,888
of 361,705 outputs
Outputs of similar age from Cancer Informatics
#1
of 24 outputs
Altmetric has tracked 34,350,842 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 474 research outputs from this source. They receive a mean Attention Score of 2.7. This one has done particularly well, scoring higher than 99% 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 361,705 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 98% of its contemporaries.
We're also able to compare this research output to 24 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.