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Semi-Supervised Learning Algorithm for Identifying High-Priority DrugDrug Interactions Through Adverse Event Reports

Overview of attention for article published in IEEE Journal of Biomedical and Health Informatics, August 2019
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#13 of 1,826)
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
8 news outlets
twitter
3 X users

Readers on

mendeley
90 Mendeley
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Article details
Title
Semi-Supervised Learning Algorithm for Identifying High-Priority DrugDrug Interactions Through Adverse Event Reports
Published in
IEEE Journal of Biomedical and Health Informatics, August 2019
DOI 10.1109/jbhi.2019.2932740
Pubmed ID
Authors

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Timeline Attention over time Attention Score history
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Activity
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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 demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 90 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 14 16%
Student > Master 9 10%
Lecturer 4 4%
Student > Doctoral Student 4 4%
Student > Bachelor 4 4%
Other 10 11%
Unknown 45 50%
Readers by discipline
Readers by discipline Count As %
Computer Science 13 14%
Pharmacology, Toxicology and Pharmaceutical Science 8 9%
Medicine and Dentistry 5 6%
Biochemistry, Genetics and Molecular Biology 4 4%
Engineering 4 4%
Other 8 9%
Unknown 48 53%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 60. 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 18 November 2019.
All research outputs
#709,231
of 25,385,509 outputs
Outputs from IEEE Journal of Biomedical and Health Informatics
#13
of 1,826 outputs
Outputs of similar age
#14,927
of 359,095 outputs
Outputs of similar age from IEEE Journal of Biomedical and Health Informatics
#1
of 29 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,826 research outputs from this source. They receive a mean Attention Score of 4.8. 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 359,095 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 95% of its contemporaries.
We're also able to compare this research output to 29 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 96% of its contemporaries.