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Machine learning in the prediction of post-stroke cognitive impairment: a systematic review and meta-analysis

Overview of attention for article published in Frontiers in Neurology, August 2023
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users

Citations

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4 Dimensions

Readers on

mendeley
15 Mendeley
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Title
Machine learning in the prediction of post-stroke cognitive impairment: a systematic review and meta-analysis
Published in
Frontiers in Neurology, August 2023
DOI 10.3389/fneur.2023.1211733
Pubmed ID
Authors

XiaoSheng Li, Zongning Chen, Hexian Jiao, BinYang Wang, Hui Yin, LuJia Chen, Hongling Shi, Yong Yin, Dongdong Qin

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 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 3 20%
Researcher 1 7%
Unknown 11 73%
Readers by discipline Count As %
Unspecified 3 20%
Biochemistry, Genetics and Molecular Biology 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 11 August 2023.
All research outputs
#19,729,060
of 24,247,965 outputs
Outputs from Frontiers in Neurology
#8,489
of 13,290 outputs
Outputs of similar age
#137,926
of 194,975 outputs
Outputs of similar age from Frontiers in Neurology
#133
of 369 outputs
Altmetric has tracked 24,247,965 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 13,290 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. 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 194,975 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 369 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.