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Artificial intelligence and avian influenza: Using machine learning to enhance active surveillance for avian influenza viruses

Overview of attention for article published in Transboundary & Emerging Diseases, August 2019
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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 (77th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

blogs
1 blog
twitter
3 X users

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
57 Mendeley
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Title
Artificial intelligence and avian influenza: Using machine learning to enhance active surveillance for avian influenza viruses
Published in
Transboundary & Emerging Diseases, August 2019
DOI 10.1111/tbed.13318
Pubmed ID
Authors

Daniel P Walsh, Ting Fung Ma, Hon S Ip, Jun Zhu

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 8 14%
Researcher 7 12%
Student > Master 6 11%
Student > Doctoral Student 3 5%
Student > Ph. D. Student 2 4%
Other 8 14%
Unknown 23 40%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 9%
Medicine and Dentistry 5 9%
Veterinary Science and Veterinary Medicine 4 7%
Mathematics 3 5%
Biochemistry, Genetics and Molecular Biology 2 4%
Other 10 18%
Unknown 28 49%
Attention Score in Context

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 17 June 2021.
All research outputs
#4,241,949
of 25,385,509 outputs
Outputs from Transboundary & Emerging Diseases
#273
of 2,134 outputs
Outputs of similar age
#77,944
of 352,137 outputs
Outputs of similar age from Transboundary & Emerging Diseases
#6
of 56 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,134 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has done well, scoring higher than 87% 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 352,137 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 77% of its contemporaries.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.