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Machine Learning for Prediction of Outcomes in Cardiogenic Shock

Overview of attention for article published in Frontiers in Cardiovascular Medicine, May 2022
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Mentioned by

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1 X user

Citations

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1 Dimensions

Readers on

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16 Mendeley
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Title
Machine Learning for Prediction of Outcomes in Cardiogenic Shock
Published in
Frontiers in Cardiovascular Medicine, May 2022
DOI 10.3389/fcvm.2022.849688
Pubmed ID
Authors

Fangning Rong, Huaqiang Xiang, Lu Qian, Yangjing Xue, Kangting Ji, Ripen Yin

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

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 3 19%
Student > Ph. D. Student 3 19%
Student > Master 3 19%
Student > Doctoral Student 1 6%
Unknown 6 38%
Readers by discipline Count As %
Unspecified 3 19%
Engineering 2 13%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Computer Science 1 6%
Biochemistry, Genetics and Molecular Biology 1 6%
Other 2 13%
Unknown 6 38%
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 10 May 2022.
All research outputs
#20,712,517
of 23,312,088 outputs
Outputs from Frontiers in Cardiovascular Medicine
#4,452
of 7,212 outputs
Outputs of similar age
#359,682
of 442,003 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#581
of 949 outputs
Altmetric has tracked 23,312,088 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 7,212 research outputs from this source. They receive a mean Attention Score of 4.3. 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 442,003 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 949 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.