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Modeling long-term human activeness using recurrent neural networks for biometric data

Overview of attention for article published in BMC Medical Informatics and Decision Making, May 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

patent
2 patents

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
37 Mendeley
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Title
Modeling long-term human activeness using recurrent neural networks for biometric data
Published in
BMC Medical Informatics and Decision Making, May 2017
DOI 10.1186/s12911-017-0453-1
Pubmed ID
Authors

Zae Myung Kim, Hyungrai Oh, Han-Gyu Kim, Chae-Gyun Lim, Kyo-Joong Oh, Ho-Jin Choi

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 24%
Researcher 8 22%
Student > Bachelor 6 16%
Student > Doctoral Student 4 11%
Student > Master 2 5%
Other 2 5%
Unknown 6 16%
Readers by discipline Count As %
Computer Science 6 16%
Medicine and Dentistry 5 14%
Engineering 4 11%
Nursing and Health Professions 4 11%
Sports and Recreations 3 8%
Other 8 22%
Unknown 7 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 01 November 2022.
All research outputs
#7,542,164
of 23,009,818 outputs
Outputs from BMC Medical Informatics and Decision Making
#780
of 2,007 outputs
Outputs of similar age
#120,171
of 313,801 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#14
of 35 outputs
Altmetric has tracked 23,009,818 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,007 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 58% 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 313,801 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.