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Comparison between machine learning methods for mortality prediction for sepsis patients with different social determinants

Overview of attention for article published in BMC Medical Informatics and Decision Making, June 2022
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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 (87th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

news
1 news outlet
blogs
1 blog

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
30 Mendeley
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Title
Comparison between machine learning methods for mortality prediction for sepsis patients with different social determinants
Published in
BMC Medical Informatics and Decision Making, June 2022
DOI 10.1186/s12911-022-01871-0
Pubmed ID
Authors

Hanyin Wang, Yikuan Li, Andrew Naidech, Yuan Luo

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 6 20%
Student > Ph. D. Student 4 13%
Researcher 3 10%
Other 1 3%
Student > Doctoral Student 1 3%
Other 6 20%
Unknown 9 30%
Readers by discipline Count As %
Unspecified 6 20%
Medicine and Dentistry 5 17%
Computer Science 3 10%
Immunology and Microbiology 1 3%
Business, Management and Accounting 1 3%
Other 2 7%
Unknown 12 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 01 June 2023.
All research outputs
#2,606,638
of 23,920,246 outputs
Outputs from BMC Medical Informatics and Decision Making
#185
of 2,042 outputs
Outputs of similar age
#52,985
of 417,124 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#5
of 57 outputs
Altmetric has tracked 23,920,246 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,042 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 90% 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 417,124 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 87% of its contemporaries.
We're also able to compare this research output to 57 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 92% of its contemporaries.