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A deep learning approach identifies new ECG features in congenital long QT syndrome

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

twitter
3 tweeters

Citations

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1 Dimensions

Readers on

mendeley
2 Mendeley
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Title
A deep learning approach identifies new ECG features in congenital long QT syndrome
Published in
BMC Medicine, May 2022
DOI 10.1186/s12916-022-02350-z
Pubmed ID
Authors

Simona Aufiero, Hidde Bleijendaal, Tomas Robyns, Bert Vandenberk, Christian Krijger, Connie Bezzina, Aeilko H. Zwinderman, Arthur A. M. Wilde, Yigal M. Pinto

Twitter Demographics

The data shown below were collected from the profiles of 3 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 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 50%
Student > Doctoral Student 1 50%
Readers by discipline Count As %
Medicine and Dentistry 1 50%
Unknown 1 50%

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 28 May 2022.
All research outputs
#16,694,589
of 21,429,365 outputs
Outputs from BMC Medicine
#2,888
of 3,144 outputs
Outputs of similar age
#222,411
of 331,520 outputs
Outputs of similar age from BMC Medicine
#1
of 1 outputs
Altmetric has tracked 21,429,365 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,144 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 41.4. This one is in the 6th percentile – i.e., 6% 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 331,520 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them