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Prediction of Lumbar Drainage-Related Meningitis Based on Supervised Machine Learning Algorithms

Overview of attention for article published in Frontiers in Public Health, June 2022
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2 X users

Citations

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3 Dimensions

Readers on

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6 Mendeley
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Title
Prediction of Lumbar Drainage-Related Meningitis Based on Supervised Machine Learning Algorithms
Published in
Frontiers in Public Health, June 2022
DOI 10.3389/fpubh.2022.910479
Pubmed ID
Authors

Peng Wang, Shuwen Cheng, Yaxin Li, Li Liu, Jia Liu, Qiang Zhao, Shuang Luo

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

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 5 83%
Unknown 1 17%
Readers by discipline Count As %
Unspecified 5 83%
Unknown 1 17%
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 15 July 2022.
All research outputs
#21,566,851
of 26,473,472 outputs
Outputs from Frontiers in Public Health
#8,498
of 14,996 outputs
Outputs of similar age
#335,099
of 447,579 outputs
Outputs of similar age from Frontiers in Public Health
#684
of 1,284 outputs
Altmetric has tracked 26,473,472 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 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 28th percentile – i.e., 28% 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 447,579 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,284 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.