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Automated Multiclass Artifact Detection in Diffusion MRI Volumes via 3D Residual Squeeze-and-Excitation Convolutional Neural Networks

Overview of attention for article published in Frontiers in Human Neuroscience, March 2022
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1 X user

Citations

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Title
Automated Multiclass Artifact Detection in Diffusion MRI Volumes via 3D Residual Squeeze-and-Excitation Convolutional Neural Networks
Published in
Frontiers in Human Neuroscience, March 2022
DOI 10.3389/fnhum.2022.877326
Pubmed ID
Authors

Nabil Ettehadi, Pratik Kashyap, Xuzhe Zhang, Yun Wang, David Semanek, Karan Desai, Jia Guo, Jonathan Posner, Andrew F. Laine

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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 12%
Student > Bachelor 1 6%
Unspecified 1 6%
Unknown 13 76%
Readers by discipline Count As %
Unspecified 1 6%
Biochemistry, Genetics and Molecular Biology 1 6%
Nursing and Health Professions 1 6%
Medicine and Dentistry 1 6%
Unknown 13 76%
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 12 April 2022.
All research outputs
#20,897,310
of 23,523,017 outputs
Outputs from Frontiers in Human Neuroscience
#6,659
of 7,308 outputs
Outputs of similar age
#361,708
of 443,527 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#155
of 178 outputs
Altmetric has tracked 23,523,017 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 7,308 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. 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 443,527 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 178 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.