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Semi-Supervised Support Vector Machine for Digital Twins Based Brain Image Fusion

Overview of attention for article published in Frontiers in Neuroscience, July 2021
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2 X users

Citations

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158 Dimensions

Readers on

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60 Mendeley
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Title
Semi-Supervised Support Vector Machine for Digital Twins Based Brain Image Fusion
Published in
Frontiers in Neuroscience, July 2021
DOI 10.3389/fnins.2021.705323
Pubmed ID
Authors

Zhibo Wan, Youqiang Dong, Zengchen Yu, Haibin Lv, Zhihan Lv

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 60 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 5 8%
Researcher 4 7%
Student > Ph. D. Student 4 7%
Other 3 5%
Student > Bachelor 3 5%
Other 8 13%
Unknown 33 55%
Readers by discipline Count As %
Computer Science 9 15%
Engineering 4 7%
Business, Management and Accounting 3 5%
Nursing and Health Professions 1 2%
Agricultural and Biological Sciences 1 2%
Other 5 8%
Unknown 37 62%
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 22 July 2021.
All research outputs
#20,509,284
of 26,069,033 outputs
Outputs from Frontiers in Neuroscience
#8,989
of 11,750 outputs
Outputs of similar age
#324,111
of 453,494 outputs
Outputs of similar age from Frontiers in Neuroscience
#301
of 408 outputs
Altmetric has tracked 26,069,033 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,750 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.1. This one is in the 17th percentile – i.e., 17% 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 453,494 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 408 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.