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Machine Learning Revealed Ferroptosis Features and a Novel Ferroptosis-Based Classification for Diagnosis in Acute Myocardial Infarction

Overview of attention for article published in Frontiers in Genetics, January 2022
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (60th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
19 Mendeley
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Title
Machine Learning Revealed Ferroptosis Features and a Novel Ferroptosis-Based Classification for Diagnosis in Acute Myocardial Infarction
Published in
Frontiers in Genetics, January 2022
DOI 10.3389/fgene.2022.813438
Pubmed ID
Authors

Dan Huang, Shiya Zheng, Zhuyuan Liu, Kongbo Zhu, Hong Zhi, Genshan Ma

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 16%
Student > Ph. D. Student 2 11%
Professor 1 5%
Researcher 1 5%
Unspecified 1 5%
Other 0 0%
Unknown 11 58%
Readers by discipline Count As %
Medicine and Dentistry 3 16%
Computer Science 2 11%
Biochemistry, Genetics and Molecular Biology 1 5%
Unspecified 1 5%
Business, Management and Accounting 1 5%
Other 0 0%
Unknown 11 58%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 February 2022.
All research outputs
#13,121,415
of 23,130,383 outputs
Outputs from Frontiers in Genetics
#2,799
of 12,169 outputs
Outputs of similar age
#196,115
of 504,490 outputs
Outputs of similar age from Frontiers in Genetics
#137
of 807 outputs
Altmetric has tracked 23,130,383 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,169 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done well, scoring higher than 75% 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 504,490 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 60% of its contemporaries.
We're also able to compare this research output to 807 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.