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American College of Cardiology

Article Metrics

Cardiac Rhythm Device Identification Using Neural Networks

Overview of attention for article published in JACC: Clinical Electrophysiology, May 2019
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#7 of 685)
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
6 news outlets
twitter
99 tweeters

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
30 Mendeley
Title
Cardiac Rhythm Device Identification Using Neural Networks
Published in
JACC: Clinical Electrophysiology, May 2019
DOI 10.1016/j.jacep.2019.02.003
Pubmed ID
Authors

James P. Howard, Louis Fisher, Matthew J. Shun-Shin, Daniel Keene, Ahran D. Arnold, Yousif Ahmad, Christopher M. Cook, James C. Moon, Charlotte H. Manisty, Zach I. Whinnett, Graham D. Cole, Daniel Rueckert, Darrel P. Francis

Twitter Demographics

The data shown below were collected from the profiles of 99 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 20%
Student > Master 5 17%
Other 3 10%
Researcher 2 7%
Librarian 1 3%
Other 3 10%
Unknown 10 33%
Readers by discipline Count As %
Medicine and Dentistry 12 40%
Computer Science 4 13%
Engineering 4 13%
Physics and Astronomy 1 3%
Agricultural and Biological Sciences 1 3%
Other 0 0%
Unknown 8 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 106. 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 February 2020.
All research outputs
#166,404
of 14,334,967 outputs
Outputs from JACC: Clinical Electrophysiology
#7
of 685 outputs
Outputs of similar age
#5,901
of 264,554 outputs
Outputs of similar age from JACC: Clinical Electrophysiology
#1
of 54 outputs
Altmetric has tracked 14,334,967 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 685 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.3. This one has done particularly well, scoring higher than 98% 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 264,554 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 97% of its contemporaries.
We're also able to compare this research output to 54 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.