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A Novel Diagnostic Prediction Model for Vestibular Migraine

Overview of attention for article published in Neuropsychiatric Disease and Treatment, July 2020
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Mentioned by

facebook
1 Facebook page

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
12 Mendeley
Title
<p>A Novel Diagnostic Prediction Model for Vestibular Migraine</p>
Published in
Neuropsychiatric Disease and Treatment, July 2020
DOI 10.2147/ndt.s255717
Authors

Chang Zhou, Lei Zhang, Xuemei Jiang, Shanshan Shi, Qiuhong Yu, Qihui Chen, Dan Yao, Yonghui Pan

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 25%
Student > Postgraduate 2 17%
Researcher 2 17%
Professor 1 8%
Professor > Associate Professor 1 8%
Other 1 8%
Unknown 2 17%
Readers by discipline Count As %
Medicine and Dentistry 3 25%
Psychology 2 17%
Social Sciences 1 8%
Environmental Science 1 8%
Neuroscience 1 8%
Other 0 0%
Unknown 4 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 28 July 2020.
All research outputs
#16,304,301
of 18,439,562 outputs
Outputs from Neuropsychiatric Disease and Treatment
#2,176
of 2,727 outputs
Outputs of similar age
#256,902
of 304,261 outputs
Outputs of similar age from Neuropsychiatric Disease and Treatment
#3
of 3 outputs
Altmetric has tracked 18,439,562 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 2,727 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. 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 304,261 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 3 others from the same source and published within six weeks on either side of this one.