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MoDL-MUSSELS: Model-Based Deep Learning for Multishot Sensitivity-Encoded Diffusion MRI

Overview of attention for article published in IEEE Transactions on Medical Imaging, October 2019
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
7 X users

Readers on

mendeley
70 Mendeley
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Article details
Title
MoDL-MUSSELS: Model-Based Deep Learning for Multishot Sensitivity-Encoded Diffusion MRI
Published in
IEEE Transactions on Medical Imaging, October 2019
DOI 10.1109/tmi.2019.2946501
Pubmed ID
Authors

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Timeline Attention over time Attention Score history
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Activity
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X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 70 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 11 16%
Student > Ph. D. Student 10 14%
Student > Master 6 9%
Lecturer 4 6%
Student > Doctoral Student 4 6%
Other 10 14%
Unknown 25 36%
Readers by discipline
Readers by discipline Count As %
Engineering 19 27%
Computer Science 5 7%
Biochemistry, Genetics and Molecular Biology 2 3%
Physics and Astronomy 2 3%
Medicine and Dentistry 2 3%
Other 6 9%
Unknown 34 49%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 23 October 2019.
All research outputs
#9,507,777
of 27,749,472 outputs
Outputs from IEEE Transactions on Medical Imaging
#1,641
of 3,889 outputs
Outputs of similar age
#148,808
of 370,884 outputs
Outputs of similar age from IEEE Transactions on Medical Imaging
#19
of 45 outputs
Altmetric has tracked 27,749,472 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,889 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 23rd percentile – i.e., 23% 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 370,884 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 45 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.