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Machine learning for diagnosis of myocardial infarction using cardiac troponin concentrations

Overview of attention for article published in Nature Medicine, May 2023
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
248 news outlets
blogs
4 blogs
twitter
161 X users
facebook
1 Facebook page

Citations

dimensions_citation
23 Dimensions

Readers on

mendeley
59 Mendeley
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Title
Machine learning for diagnosis of myocardial infarction using cardiac troponin concentrations
Published in
Nature Medicine, May 2023
DOI 10.1038/s41591-023-02325-4
Pubmed ID
Authors

Dimitrios Doudesis, Kuan Ken Lee, Jasper Boeddinghaus, Anda Bularga, Amy V. Ferry, Chris Tuck, Matthew T. H. Lowry, Pedro Lopez-Ayala, Thomas Nestelberger, Luca Koechlin, Miguel O. Bernabeu, Lis Neubeck, Atul Anand, Karen Schulz, Fred S. Apple, William Parsonage, Jaimi H. Greenslade, Louise Cullen, John W. Pickering, Martin P. Than, Alasdair Gray, Christian Mueller, Nicholas L. Mills

X Demographics

X Demographics

The data shown below were collected from the profiles of 161 X users 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 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 59 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 5 8%
Student > Master 5 8%
Student > Doctoral Student 4 7%
Other 4 7%
Professor 3 5%
Other 11 19%
Unknown 27 46%
Readers by discipline Count As %
Medicine and Dentistry 10 17%
Unspecified 5 8%
Biochemistry, Genetics and Molecular Biology 4 7%
Engineering 3 5%
Computer Science 2 3%
Other 8 14%
Unknown 27 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1944. 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 29 August 2023.
All research outputs
#4,938
of 25,791,495 outputs
Outputs from Nature Medicine
#82
of 9,435 outputs
Outputs of similar age
#129
of 405,098 outputs
Outputs of similar age from Nature Medicine
#2
of 155 outputs
Altmetric has tracked 25,791,495 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,435 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 103.9. This one has done particularly well, scoring higher than 99% 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 405,098 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 155 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.