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A markup language for electrocardiogram data acquisition and analysis (ecgML)

Overview of attention for article published in BMC Medical Informatics and Decision Making, May 2003
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Citations

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Title
A markup language for electrocardiogram data acquisition and analysis (ecgML)
Published in
BMC Medical Informatics and Decision Making, May 2003
DOI 10.1186/1472-6947-3-4
Pubmed ID
Authors

Haiying Wang, Francisco Azuaje, Benjamin Jung, Norman Black

Abstract

The storage and distribution of electrocardiogram data is based on different formats. There is a need to promote the development of standards for their exchange and analysis. Such models should be platform-/ system- and application-independent, flexible and open to every member of the scientific community.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 25%
Student > Bachelor 1 25%
Researcher 1 25%
Student > Master 1 25%
Readers by discipline Count As %
Computer Science 1 25%
Social Sciences 1 25%
Medicine and Dentistry 1 25%
Engineering 1 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 21 June 2014.
All research outputs
#18,373,874
of 22,757,541 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,567
of 1,985 outputs
Outputs of similar age
#48,010
of 50,495 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#3
of 4 outputs
Altmetric has tracked 22,757,541 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,985 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 9th percentile – i.e., 9% of its peers scored the same or lower than it.
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 50,495 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one.