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Identifying key genes related to inflammasome in severe COVID-19 patients based on a joint model with random forest and artificial neural network

Overview of attention for article published in Frontiers in Cellular and Infection Microbiology, April 2023
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

twitter
6 X users

Citations

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6 Dimensions

Readers on

mendeley
10 Mendeley
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Title
Identifying key genes related to inflammasome in severe COVID-19 patients based on a joint model with random forest and artificial neural network
Published in
Frontiers in Cellular and Infection Microbiology, April 2023
DOI 10.3389/fcimb.2023.1139998
Pubmed ID
Authors

Haiya Ou, Yaohua Fan, Xiaoxuan Guo, Zizhao Lao, Meiling Zhu, Geng Li, Lijun Zhao

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 20%
Professor > Associate Professor 2 20%
Researcher 2 20%
Student > Postgraduate 1 10%
Student > Doctoral Student 1 10%
Other 0 0%
Unknown 2 20%
Readers by discipline Count As %
Unspecified 4 40%
Biochemistry, Genetics and Molecular Biology 2 20%
Pharmacology, Toxicology and Pharmaceutical Science 1 10%
Nursing and Health Professions 1 10%
Unknown 2 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 21 May 2023.
All research outputs
#8,409,604
of 25,941,588 outputs
Outputs from Frontiers in Cellular and Infection Microbiology
#1,871
of 8,329 outputs
Outputs of similar age
#145,349
of 425,849 outputs
Outputs of similar age from Frontiers in Cellular and Infection Microbiology
#63
of 455 outputs
Altmetric has tracked 25,941,588 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 8,329 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done well, scoring higher than 77% of its peers.
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 425,849 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 455 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.