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A Risk-Stratification Machine Learning Framework for the Prediction of Coronary Artery Disease Severity: Insights From the GESS Trial

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

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
1 X user
patent
1 patent

Citations

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17 Dimensions

Readers on

mendeley
33 Mendeley
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Title
A Risk-Stratification Machine Learning Framework for the Prediction of Coronary Artery Disease Severity: Insights From the GESS Trial
Published in
Frontiers in Cardiovascular Medicine, January 2022
DOI 10.3389/fcvm.2021.812182
Pubmed ID
Authors

Nikolaos Mittas, Fani Chatzopoulou, Konstantinos A. Kyritsis, Christos I. Papagiannopoulos, Nikoleta F. Theodoroula, Andreas S. Papazoglou, Efstratios Karagiannidis, Georgios Sofidis, Dimitrios V. Moysidis, Nikolaos Stalikas, Anna Papa, Dimitrios Chatzidimitriou, Georgios Sianos, Lefteris Angelis, Ioannis S. Vizirianakis

Timeline

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

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 9%
Researcher 3 9%
Unspecified 2 6%
Professor 2 6%
Lecturer 2 6%
Other 2 6%
Unknown 19 58%
Readers by discipline Count As %
Medicine and Dentistry 3 9%
Biochemistry, Genetics and Molecular Biology 2 6%
Unspecified 2 6%
Environmental Science 1 3%
Business, Management and Accounting 1 3%
Other 4 12%
Unknown 20 61%
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 06 June 2024.
All research outputs
#8,623,414
of 26,268,316 outputs
Outputs from Frontiers in Cardiovascular Medicine
#1,588
of 9,474 outputs
Outputs of similar age
#186,035
of 531,044 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#155
of 818 outputs
Altmetric has tracked 26,268,316 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 9,474 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done well, scoring higher than 82% 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 531,044 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 64% of its contemporaries.
We're also able to compare this research output to 818 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.