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A Bayesian network-based approach for identifying risk factors and predicting ischemic stroke in infective endocarditis patients

Overview of attention for article published in Frontiers in Cardiovascular Medicine, January 2024
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2 X users

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3 Mendeley
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Title
A Bayesian network-based approach for identifying risk factors and predicting ischemic stroke in infective endocarditis patients
Published in
Frontiers in Cardiovascular Medicine, January 2024
DOI 10.3389/fcvm.2023.1294229
Pubmed ID
Authors

Boyi Yuan, Chaobin Wang, Zexin Fan, Chun Liu, Libo Fang, Lin Ma, Wenlong Zou, Guobin Yuan, Guangzhi Liu

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.
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%
Medicine and Dentistry 1 33%
Engineering 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 07 January 2024.
All research outputs
#20,440,927
of 25,121,016 outputs
Outputs from Frontiers in Cardiovascular Medicine
#4,329
of 8,970 outputs
Outputs of similar age
#115,111
of 168,196 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#79
of 225 outputs
Altmetric has tracked 25,121,016 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 8,970 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 37th percentile – i.e., 37% 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 168,196 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 225 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.