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Machine Learning Algorithms to Distinguish Myocardial Perfusion SPECT Polar Maps

Overview of attention for article published in Frontiers in Cardiovascular Medicine, November 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
7 X users

Citations

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8 Dimensions

Readers on

mendeley
12 Mendeley
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Title
Machine Learning Algorithms to Distinguish Myocardial Perfusion SPECT Polar Maps
Published in
Frontiers in Cardiovascular Medicine, November 2021
DOI 10.3389/fcvm.2021.741667
Pubmed ID
Authors

Erito Marques de Souza Filho, Fernando de Amorim Fernandes, Christiane Wiefels, Lucas Nunes Dalbonio de Carvalho, Tadeu Francisco dos Santos, Alair Augusto Sarmet M. D. dos Santos, Evandro Tinoco Mesquita, Flávio Luiz Seixas, Benjamin J. W. Chow, Claudio Tinoco Mesquita, Ronaldo Altenburg Gismondi

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X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Professor 4 33%
Researcher 3 25%
Student > Ph. D. Student 1 8%
Librarian 1 8%
Unknown 3 25%
Readers by discipline Count As %
Medicine and Dentistry 2 17%
Computer Science 2 17%
Engineering 2 17%
Pharmacology, Toxicology and Pharmaceutical Science 1 8%
Design 1 8%
Other 0 0%
Unknown 4 33%
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 17 April 2022.
All research outputs
#8,952,648
of 26,556,052 outputs
Outputs from Frontiers in Cardiovascular Medicine
#1,708
of 9,579 outputs
Outputs of similar age
#165,106
of 445,562 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#155
of 794 outputs
Altmetric has tracked 26,556,052 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 9,579 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done well, scoring higher than 81% 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 445,562 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 62% of its contemporaries.
We're also able to compare this research output to 794 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.