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Mobile GPU-based implementation of automatic analysis method for long-term ECG

Overview of attention for article published in BioMedical Engineering OnLine, May 2018
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
33 Mendeley
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Title
Mobile GPU-based implementation of automatic analysis method for long-term ECG
Published in
BioMedical Engineering OnLine, May 2018
DOI 10.1186/s12938-018-0487-3
Pubmed ID
Authors

Xiaomao Fan, Qihang Yao, Ye Li, Runge Chen, Yunpeng Cai

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 18%
Student > Ph. D. Student 5 15%
Student > Master 3 9%
Professor 3 9%
Researcher 2 6%
Other 3 9%
Unknown 11 33%
Readers by discipline Count As %
Engineering 6 18%
Computer Science 5 15%
Medicine and Dentistry 4 12%
Physics and Astronomy 2 6%
Earth and Planetary Sciences 1 3%
Other 2 6%
Unknown 13 39%
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 04 August 2021.
All research outputs
#7,656,930
of 23,310,485 outputs
Outputs from BioMedical Engineering OnLine
#217
of 834 outputs
Outputs of similar age
#131,310
of 327,150 outputs
Outputs of similar age from BioMedical Engineering OnLine
#4
of 15 outputs
Altmetric has tracked 23,310,485 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 834 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 61% 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 327,150 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 53% of its contemporaries.
We're also able to compare this research output to 15 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 66% of its contemporaries.