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Helicobacter pylori (H. pylori) risk factor analysis and prevalence prediction: a machine learning-based approach

Overview of attention for article published in BMC Infectious Diseases, July 2022
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Mentioned by

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1 X user

Citations

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9 Dimensions

Readers on

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34 Mendeley
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Title
Helicobacter pylori (H. pylori) risk factor analysis and prevalence prediction: a machine learning-based approach
Published in
BMC Infectious Diseases, July 2022
DOI 10.1186/s12879-022-07625-7
Pubmed ID
Authors

Van Tran, Tazmilur Saad, Mehret Tesfaye, Sosina Walelign, Moges Wordofa, Dessie Abera, Kassu Desta, Aster Tsegaye, Ahmet Ay, Bineyam Taye

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

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 9%
Student > Ph. D. Student 2 6%
Researcher 2 6%
Student > Doctoral Student 1 3%
Unspecified 1 3%
Other 1 3%
Unknown 24 71%
Readers by discipline Count As %
Medicine and Dentistry 3 9%
Biochemistry, Genetics and Molecular Biology 3 9%
Immunology and Microbiology 2 6%
Environmental Science 1 3%
Unspecified 1 3%
Other 2 6%
Unknown 22 65%
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 28 July 2022.
All research outputs
#21,392,871
of 23,885,338 outputs
Outputs from BMC Infectious Diseases
#6,779
of 8,002 outputs
Outputs of similar age
#348,821
of 418,578 outputs
Outputs of similar age from BMC Infectious Diseases
#132
of 150 outputs
Altmetric has tracked 23,885,338 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 8,002 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. 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 418,578 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 150 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.