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Bibliometric and visual analysis of machine learning-based research in acute kidney injury worldwide

Overview of attention for article published in Frontiers in Public Health, March 2023
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Mentioned by

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1 X user

Citations

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4 Dimensions

Readers on

mendeley
18 Mendeley
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Title
Bibliometric and visual analysis of machine learning-based research in acute kidney injury worldwide
Published in
Frontiers in Public Health, March 2023
DOI 10.3389/fpubh.2023.1136939
Pubmed ID
Authors

Xiang Yu, RiLiGe Wu, YuWei Ji, Zhe Feng

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

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Other 2 11%
Librarian 1 6%
Lecturer > Senior Lecturer 1 6%
Student > Ph. D. Student 1 6%
Researcher 1 6%
Other 0 0%
Unknown 12 67%
Readers by discipline Count As %
Computer Science 2 11%
Medicine and Dentistry 2 11%
Unknown 14 78%
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 17 March 2023.
All research outputs
#23,784,760
of 26,473,472 outputs
Outputs from Frontiers in Public Health
#10,725
of 14,996 outputs
Outputs of similar age
#383,228
of 445,246 outputs
Outputs of similar age from Frontiers in Public Health
#606
of 1,103 outputs
Altmetric has tracked 26,473,472 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 14,996 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. 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 445,246 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 1,103 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.