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Multiphase CT-based prediction of Child-Pugh classification: a machine learning approach

Overview of attention for article published in European Radiology Experimental, April 2020
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Mentioned by

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1 X user

Citations

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Readers on

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30 Mendeley
Title
Multiphase CT-based prediction of Child-Pugh classification: a machine learning approach
Published in
European Radiology Experimental, April 2020
DOI 10.1186/s41747-020-00148-3
Pubmed ID
Authors

Johannes Thüring, Oliver Rippel, Christoph Haarburger, Dorit Merhof, Philipp Schad, Philipp Bruners, Christiane K. Kuhl, Daniel Truhn

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 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 %
Student > Master 4 13%
Researcher 4 13%
Student > Doctoral Student 3 10%
Lecturer 2 7%
Student > Ph. D. Student 2 7%
Other 5 17%
Unknown 10 33%
Readers by discipline Count As %
Medicine and Dentistry 13 43%
Computer Science 2 7%
Immunology and Microbiology 1 3%
Social Sciences 1 3%
Engineering 1 3%
Other 0 0%
Unknown 12 40%
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 08 April 2020.
All research outputs
#20,612,116
of 23,201,298 outputs
Outputs from European Radiology Experimental
#178
of 205 outputs
Outputs of similar age
#318,731
of 373,116 outputs
Outputs of similar age from European Radiology Experimental
#12
of 12 outputs
Altmetric has tracked 23,201,298 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 205 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.5. 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 373,116 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 12 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.