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Use of Machine Learning and Statistical Algorithms to Predict Hospital Length of Stay Following Colorectal Cancer Resection: A South African Pilot Study

Overview of attention for article published in Frontiers in oncology, October 2021
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
3 X users

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
21 Mendeley
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Title
Use of Machine Learning and Statistical Algorithms to Predict Hospital Length of Stay Following Colorectal Cancer Resection: A South African Pilot Study
Published in
Frontiers in oncology, October 2021
DOI 10.3389/fonc.2021.644045
Pubmed ID
Authors

Okechinyere J. Achilonu, June Fabian, Brendan Bebington, Elvira Singh, Gideon Nimako, Rene M. J. C. Eijkemans, Eustasius Musenge

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 14%
Researcher 3 14%
Student > Bachelor 2 10%
Librarian 1 5%
Other 1 5%
Other 4 19%
Unknown 7 33%
Readers by discipline Count As %
Medicine and Dentistry 5 24%
Unspecified 1 5%
Pharmacology, Toxicology and Pharmaceutical Science 1 5%
Business, Management and Accounting 1 5%
Arts and Humanities 1 5%
Other 4 19%
Unknown 8 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 18 October 2021.
All research outputs
#15,751,285
of 25,392,582 outputs
Outputs from Frontiers in oncology
#4,979
of 22,436 outputs
Outputs of similar age
#220,762
of 436,541 outputs
Outputs of similar age from Frontiers in oncology
#256
of 1,446 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,436 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done well, scoring higher than 75% 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 436,541 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,446 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.