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Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort

Overview of attention for article published in Critical Care, August 2021
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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 (80th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
19 X users

Citations

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41 Dimensions

Readers on

mendeley
102 Mendeley
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Title
Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort
Published in
Critical Care, August 2021
DOI 10.1186/s13054-021-03720-4
Pubmed ID
Authors

Harry Magunia, Simone Lederer, Raphael Verbuecheln, Bryant Joseph Gilot, Michael Koeppen, Helene A. Haeberle, Valbona Mirakaj, Pascal Hofmann, Gernot Marx, Johannes Bickenbach, Boris Nohe, Michael Lay, Claudia Spies, Andreas Edel, Fridtjof Schiefenhövel, Tim Rahmel, Christian Putensen, Timur Sellmann, Thea Koch, Timo Brandenburger, Detlef Kindgen-Milles, Thorsten Brenner, Marc Berger, Kai Zacharowski, Elisabeth Adam, Matthias Posch, Onnen Moerer, Christian S. Scheer, Daniel Sedding, Markus A. Weigand, Falk Fichtner, Carla Nau, Florian Prätsch, Thomas Wiesmann, Christian Koch, Gerhard Schneider, Tobias Lahmer, Andreas Straub, Andreas Meiser, Manfred Weiss, Bettina Jungwirth, Frank Wappler, Patrick Meybohm, Johannes Herrmann, Nisar Malek, Oliver Kohlbacher, Stephanie Biergans, Peter Rosenberger

X Demographics

X Demographics

The data shown below were collected from the profiles of 19 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 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 102 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 13%
Student > Ph. D. Student 10 10%
Student > Bachelor 10 10%
Student > Master 6 6%
Student > Doctoral Student 6 6%
Other 17 17%
Unknown 40 39%
Readers by discipline Count As %
Medicine and Dentistry 21 21%
Engineering 10 10%
Nursing and Health Professions 6 6%
Computer Science 5 5%
Economics, Econometrics and Finance 3 3%
Other 15 15%
Unknown 42 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 14 January 2023.
All research outputs
#3,774,461
of 25,394,764 outputs
Outputs from Critical Care
#2,863
of 6,558 outputs
Outputs of similar age
#84,756
of 436,698 outputs
Outputs of similar age from Critical Care
#69
of 107 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,558 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.8. This one has gotten more attention than average, scoring higher than 56% 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 436,698 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 80% of its contemporaries.
We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.