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Health insurance fraud detection by using an attributed heterogeneous information network with a hierarchical attention mechanism

Overview of attention for article published in BMC Medical Informatics and Decision Making, April 2023
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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 (76th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
31 Mendeley
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Title
Health insurance fraud detection by using an attributed heterogeneous information network with a hierarchical attention mechanism
Published in
BMC Medical Informatics and Decision Making, April 2023
DOI 10.1186/s12911-023-02152-0
Pubmed ID
Authors

Jiangtao Lu, Kaibiao Lin, Ruicong Chen, Min Lin, Xin Chen, Ping Lu

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 3%
Student > Bachelor 1 3%
Student > Ph. D. Student 1 3%
Librarian 1 3%
Researcher 1 3%
Other 1 3%
Unknown 25 81%
Readers by discipline Count As %
Computer Science 2 6%
Unspecified 1 3%
Business, Management and Accounting 1 3%
Social Sciences 1 3%
Unknown 26 84%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 22 December 2023.
All research outputs
#5,013,742
of 25,038,941 outputs
Outputs from BMC Medical Informatics and Decision Making
#398
of 2,125 outputs
Outputs of similar age
#89,362
of 408,162 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#8
of 32 outputs
Altmetric has tracked 25,038,941 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,125 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done well, scoring higher than 80% 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 408,162 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 76% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.