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Antepartum fetal heart rate feature extraction and classification using empirical mode decomposition and support vector machine

Overview of attention for article published in BioMedical Engineering OnLine, January 2011
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

patent
1 patent

Citations

dimensions_citation
75 Dimensions

Readers on

mendeley
76 Mendeley
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Title
Antepartum fetal heart rate feature extraction and classification using empirical mode decomposition and support vector machine
Published in
BioMedical Engineering OnLine, January 2011
DOI 10.1186/1475-925x-10-6
Pubmed ID
Authors

Niranjana Krupa, Mohd Ali MA, Edmond Zahedi, Shuhaila Ahmed, Fauziah M Hassan

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 1%
France 1 1%
Unknown 74 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 16%
Student > Bachelor 11 14%
Student > Master 9 12%
Researcher 6 8%
Professor > Associate Professor 5 7%
Other 19 25%
Unknown 14 18%
Readers by discipline Count As %
Engineering 22 29%
Computer Science 12 16%
Medicine and Dentistry 8 11%
Agricultural and Biological Sciences 5 7%
Nursing and Health Professions 4 5%
Other 9 12%
Unknown 16 21%
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 15 August 2019.
All research outputs
#8,534,528
of 25,371,288 outputs
Outputs from BioMedical Engineering OnLine
#238
of 867 outputs
Outputs of similar age
#59,193
of 193,491 outputs
Outputs of similar age from BioMedical Engineering OnLine
#2
of 5 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 867 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 gotten more attention than average, scoring higher than 60% 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 193,491 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.