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Combining entity co-occurrence with specialized word embeddings to measure entity relation in Alzheimer’s disease

Overview of attention for article published in BMC Medical Informatics and Decision Making, December 2019
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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 (80th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

news
1 news outlet
twitter
1 tweeter

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
15 Mendeley
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Title
Combining entity co-occurrence with specialized word embeddings to measure entity relation in Alzheimer’s disease
Published in
BMC Medical Informatics and Decision Making, December 2019
DOI 10.1186/s12911-019-0934-5
Pubmed ID
Authors

Go Eun Heo, Qing Xie, Min Song, Jeong-Hoon Lee

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 5 33%
Student > Ph. D. Student 3 20%
Researcher 2 13%
Lecturer 1 7%
Student > Master 1 7%
Other 0 0%
Unknown 3 20%
Readers by discipline Count As %
Unspecified 5 33%
Computer Science 2 13%
Agricultural and Biological Sciences 1 7%
Social Sciences 1 7%
Medicine and Dentistry 1 7%
Other 1 7%
Unknown 4 27%

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 December 2019.
All research outputs
#1,966,891
of 15,226,794 outputs
Outputs from BMC Medical Informatics and Decision Making
#197
of 1,381 outputs
Outputs of similar age
#68,298
of 346,531 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#31
of 162 outputs
Altmetric has tracked 15,226,794 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,381 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done well, scoring higher than 85% 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 346,531 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 80% of its contemporaries.
We're also able to compare this research output to 162 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.