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Integrated Blockchain-Deep Learning Approach for Analyzing the Electronic Health Records Recommender System

Overview of attention for article published in Frontiers in Public Health, May 2022
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

twitter
12 X users
peer_reviews
1 peer review site

Readers on

mendeley
47 Mendeley
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Title
Integrated Blockchain-Deep Learning Approach for Analyzing the Electronic Health Records Recommender System
Published in
Frontiers in Public Health, May 2022
DOI 10.3389/fpubh.2022.905265
Pubmed ID
Authors

Eric Appiah Mantey, Conghua Zhou, S. R. Srividhya, Sanjiv Kumar Jain, B. Sundaravadivazhagan

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 10 21%
Student > Ph. D. Student 5 11%
Unspecified 3 6%
Student > Master 3 6%
Student > Doctoral Student 2 4%
Other 4 9%
Unknown 20 43%
Readers by discipline Count As %
Computer Science 15 32%
Unspecified 3 6%
Engineering 3 6%
Biochemistry, Genetics and Molecular Biology 1 2%
Medicine and Dentistry 1 2%
Other 3 6%
Unknown 21 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 13 July 2023.
All research outputs
#3,903,432
of 26,473,472 outputs
Outputs from Frontiers in Public Health
#1,969
of 14,996 outputs
Outputs of similar age
#83,105
of 451,993 outputs
Outputs of similar age from Frontiers in Public Health
#118
of 1,125 outputs
Altmetric has tracked 26,473,472 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,996 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has done well, scoring higher than 86% 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 451,993 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 81% of its contemporaries.
We're also able to compare this research output to 1,125 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.