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Machine learning decision tree models for multiclass classification of common malignant brain tumors using perfusion and spectroscopy MRI data

Overview of attention for article published in Frontiers in oncology, August 2023
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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2 X users

Citations

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3 Dimensions

Readers on

mendeley
8 Mendeley
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Title
Machine learning decision tree models for multiclass classification of common malignant brain tumors using perfusion and spectroscopy MRI data
Published in
Frontiers in oncology, August 2023
DOI 10.3389/fonc.2023.1089998
Pubmed ID
Authors

Rodolphe Vallée, Jean-Noël Vallée, Carole Guillevin, Athéna Lallouette, Clément Thomas, Guillaume Rittano, Michel Wager, Rémy Guillevin, Alexandre Vallée

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 13%
Student > Bachelor 1 13%
Researcher 1 13%
Unknown 5 63%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 13%
Neuroscience 1 13%
Medicine and Dentistry 1 13%
Unknown 5 63%
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 15 August 2023.
All research outputs
#21,330,066
of 26,181,776 outputs
Outputs from Frontiers in oncology
#11,713
of 22,924 outputs
Outputs of similar age
#265,612
of 365,563 outputs
Outputs of similar age from Frontiers in oncology
#341
of 1,012 outputs
Altmetric has tracked 26,181,776 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,924 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 28th percentile – i.e., 28% 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 365,563 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,012 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.