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Human vs. Machine Learning Based Detection of Facial Weakness Using Video Analysis

Overview of attention for article published in Frontiers in Neurology, July 2022
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Mentioned by

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2 X users

Citations

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3 Dimensions

Readers on

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15 Mendeley
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Title
Human vs. Machine Learning Based Detection of Facial Weakness Using Video Analysis
Published in
Frontiers in Neurology, July 2022
DOI 10.3389/fneur.2022.878282
Pubmed ID
Authors

Chad M. Aldridge, Mark M. McDonald, Mattia Wruble, Yan Zhuang, Omar Uribe, Timothy L. McMurry, Iris Lin, Haydon Pitchford, Brett J. Schneider, William A. Dalrymple, Joseph F. Carrera, Sherita Chapman, Bradford B. Worrall, Gustavo K. Rohde, Andrew M. Southerland

Timeline

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

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 13%
Student > Bachelor 2 13%
Unknown 11 73%
Readers by discipline Count As %
Unspecified 2 13%
Biochemistry, Genetics and Molecular Biology 1 7%
Medicine and Dentistry 1 7%
Unknown 11 73%
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 18 July 2022.
All research outputs
#18,465,704
of 22,880,230 outputs
Outputs from Frontiers in Neurology
#7,774
of 11,802 outputs
Outputs of similar age
#305,840
of 436,537 outputs
Outputs of similar age from Frontiers in Neurology
#390
of 789 outputs
Altmetric has tracked 22,880,230 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,802 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one is in the 25th percentile – i.e., 25% 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 436,537 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 789 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.