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Impact of the Covid-19 pandemic on the performance of machine learning algorithms for predicting perioperative mortality

Overview of attention for article published in BMC Medical Informatics and Decision Making, April 2023
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Mentioned by

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1 X user

Citations

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1 Dimensions

Readers on

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9 Mendeley
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Title
Impact of the Covid-19 pandemic on the performance of machine learning algorithms for predicting perioperative mortality
Published in
BMC Medical Informatics and Decision Making, April 2023
DOI 10.1186/s12911-023-02151-1
Pubmed ID
Authors

D. I. Andonov, B. Ulm, M. Graessner, A. Podtschaske, M. Blobner, B. Jungwirth, S. M. Kagerbauer

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 33%
Librarian 1 11%
Student > Bachelor 1 11%
Student > Master 1 11%
Unknown 3 33%
Readers by discipline Count As %
Medicine and Dentistry 3 33%
Computer Science 1 11%
Unknown 5 56%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 02 June 2023.
All research outputs
#21,288,574
of 23,917,011 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,856
of 2,041 outputs
Outputs of similar age
#322,476
of 407,911 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#23
of 28 outputs
Altmetric has tracked 23,917,011 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,041 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 407,911 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.