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Application of artificial intelligence ensemble learning model in early prediction of atrial fibrillation

Overview of attention for article published in BMC Bioinformatics, November 2021
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

news
1 news outlet
twitter
10 tweeters

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
13 Mendeley
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Title
Application of artificial intelligence ensemble learning model in early prediction of atrial fibrillation
Published in
BMC Bioinformatics, November 2021
DOI 10.1186/s12859-021-04000-2
Pubmed ID
Authors

Cai Wu, Maxwell Hwang, Tian-Hsiang Huang, Yen-Ming J. Chen, Yiu-Jen Chang, Tsung-Han Ho, Jian Huang, Kao-Shing Hwang, Wen-Hsien Ho

Twitter Demographics

The data shown below were collected from the profiles of 10 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 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 23%
Student > Doctoral Student 3 23%
Lecturer 1 8%
Unknown 6 46%
Readers by discipline Count As %
Computer Science 2 15%
Nursing and Health Professions 1 8%
Medicine and Dentistry 1 8%
Neuroscience 1 8%
Engineering 1 8%
Other 0 0%
Unknown 7 54%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 30 November 2021.
All research outputs
#3,279,069
of 21,301,416 outputs
Outputs from BMC Bioinformatics
#1,231
of 6,910 outputs
Outputs of similar age
#85,656
of 420,918 outputs
Outputs of similar age from BMC Bioinformatics
#126
of 560 outputs
Altmetric has tracked 21,301,416 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,910 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. 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 420,918 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 560 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.