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Machine learning in infection management using routine electronic health records: tools, techniques, and reporting of future technologies

Overview of attention for article published in Clinical Microbiology and Infection, October 2020
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

twitter
24 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
28 Dimensions

Readers on

mendeley
137 Mendeley
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Title
Machine learning in infection management using routine electronic health records: tools, techniques, and reporting of future technologies
Published in
Clinical Microbiology and Infection, October 2020
DOI 10.1016/j.cmi.2020.02.003
Pubmed ID
Authors

C.F. Luz, M. Vollmer, J. Decruyenaere, M.W. Nijsten, C. Glasner, B. Sinha

Twitter Demographics

The data shown below were collected from the profiles of 24 tweeters 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 137 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 137 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 14%
Student > Master 19 14%
Student > Bachelor 17 12%
Student > Ph. D. Student 16 12%
Student > Doctoral Student 10 7%
Other 25 18%
Unknown 31 23%
Readers by discipline Count As %
Computer Science 25 18%
Medicine and Dentistry 22 16%
Engineering 13 9%
Nursing and Health Professions 12 9%
Unspecified 5 4%
Other 22 16%
Unknown 38 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 September 2020.
All research outputs
#1,702,725
of 18,908,606 outputs
Outputs from Clinical Microbiology and Infection
#535
of 3,744 outputs
Outputs of similar age
#46,276
of 353,408 outputs
Outputs of similar age from Clinical Microbiology and Infection
#19
of 76 outputs
Altmetric has tracked 18,908,606 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,744 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.9. This one has done well, scoring higher than 85% 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 353,408 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 76 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.