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Analysis of a deep learning-based method for generation of SPECT projections based on a large Monte Carlo simulated dataset

Overview of attention for article published in EJNMMI Physics, July 2022
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 tweeter

Readers on

mendeley
3 Mendeley
Title
Analysis of a deep learning-based method for generation of SPECT projections based on a large Monte Carlo simulated dataset
Published in
EJNMMI Physics, July 2022
DOI 10.1186/s40658-022-00476-w
Pubmed ID
Authors

Julian Leube, Johan Gustafsson, Michael Lassmann, Maikol Salas-Ramirez, Johannes Tran-Gia

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 33%
Researcher 1 33%
Other 1 33%
Readers by discipline Count As %
Physics and Astronomy 2 67%
Computer Science 1 33%

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 19 July 2022.
All research outputs
#14,977,499
of 22,270,761 outputs
Outputs from EJNMMI Physics
#70
of 171 outputs
Outputs of similar age
#189,766
of 336,711 outputs
Outputs of similar age from EJNMMI Physics
#1
of 1 outputs
Altmetric has tracked 22,270,761 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 171 research outputs from this source. They receive a mean Attention Score of 2.6. This one is in the 41st percentile – i.e., 41% 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 336,711 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them