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Diagnosis of Brain Diseases via Multi-Scale Time-Series Model

Overview of attention for article published in Frontiers in Neuroscience, March 2019
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2 X users

Citations

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6 Dimensions

Readers on

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25 Mendeley
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Title
Diagnosis of Brain Diseases via Multi-Scale Time-Series Model
Published in
Frontiers in Neuroscience, March 2019
DOI 10.3389/fnins.2019.00197
Pubmed ID
Authors

Zehua Zhang, Junhai Xu, Jijun Tang, Quan Zou, Fei Guo

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

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 28%
Student > Master 4 16%
Student > Bachelor 2 8%
Other 1 4%
Student > Doctoral Student 1 4%
Other 2 8%
Unknown 8 32%
Readers by discipline Count As %
Medicine and Dentistry 3 12%
Computer Science 2 8%
Agricultural and Biological Sciences 2 8%
Biochemistry, Genetics and Molecular Biology 2 8%
Neuroscience 2 8%
Other 4 16%
Unknown 10 40%
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 05 May 2019.
All research outputs
#20,663,600
of 25,385,509 outputs
Outputs from Frontiers in Neuroscience
#9,473
of 11,543 outputs
Outputs of similar age
#281,688
of 365,022 outputs
Outputs of similar age from Frontiers in Neuroscience
#290
of 361 outputs
Altmetric has tracked 25,385,509 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 11,543 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 11th percentile – i.e., 11% 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 365,022 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 361 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.