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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 (71st percentile)

Mentioned by

twitter
25 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
51 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 25 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 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 20%
Student > Master 8 16%
Student > Bachelor 7 14%
Student > Ph. D. Student 5 10%
Student > Doctoral Student 4 8%
Other 6 12%
Unknown 11 22%
Readers by discipline Count As %
Medicine and Dentistry 11 22%
Engineering 7 14%
Computer Science 7 14%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Nursing and Health Professions 2 4%
Other 8 16%
Unknown 14 27%

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
#1,394,784
of 16,039,351 outputs
Outputs from Clinical Microbiology and Infection
#391
of 3,279 outputs
Outputs of similar age
#40,402
of 309,948 outputs
Outputs of similar age from Clinical Microbiology and Infection
#20
of 71 outputs
Altmetric has tracked 16,039,351 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,279 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.5. This one has done well, scoring higher than 88% 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 309,948 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 71 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.