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Utilizing machine learning algorithms for the prediction of carotid artery plaques in a Chinese population

Overview of attention for article published in Frontiers in Physiology, November 2023
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Mentioned by

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1 X user

Citations

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1 Dimensions

Readers on

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3 Mendeley
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Title
Utilizing machine learning algorithms for the prediction of carotid artery plaques in a Chinese population
Published in
Frontiers in Physiology, November 2023
DOI 10.3389/fphys.2023.1295371
Pubmed ID
Authors

Shuwei Weng, Jin Chen, Chen Ding, Die Hu, Wenwu Liu, Yanyi Yang, Daoquan Peng

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 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 %
Unspecified 1 33%
Student > Master 1 33%
Unknown 1 33%
Readers by discipline Count As %
Unspecified 1 33%
Social Sciences 1 33%
Unknown 1 33%
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 06 November 2023.
All research outputs
#22,186,227
of 24,754,968 outputs
Outputs from Frontiers in Physiology
#10,285
of 15,204 outputs
Outputs of similar age
#131,367
of 165,121 outputs
Outputs of similar age from Frontiers in Physiology
#65
of 154 outputs
Altmetric has tracked 24,754,968 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 15,204 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. 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 165,121 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 154 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.