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Complexities, variations, and errors of numbering within clinical notes: the potential impact on information extraction and cohort-identification

Overview of attention for article published in BMC Medical Informatics and Decision Making, April 2019
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Mentioned by

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1 X user

Citations

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9 Dimensions

Readers on

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37 Mendeley
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Title
Complexities, variations, and errors of numbering within clinical notes: the potential impact on information extraction and cohort-identification
Published in
BMC Medical Informatics and Decision Making, April 2019
DOI 10.1186/s12911-019-0784-1
Pubmed ID
Authors

David A. Hanauer, Qiaozhu Mei, V. G. Vinod Vydiswaran, Karandeep Singh, Zach Landis-Lewis, Chunhua Weng

X Demographics

X Demographics

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 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 5 14%
Professor > Associate Professor 3 8%
Student > Bachelor 3 8%
Student > Master 2 5%
Other 7 19%
Unknown 8 22%
Readers by discipline Count As %
Computer Science 10 27%
Medicine and Dentistry 7 19%
Nursing and Health Professions 2 5%
Engineering 2 5%
Immunology and Microbiology 1 3%
Other 3 8%
Unknown 12 32%
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 05 April 2019.
All research outputs
#20,564,621
of 23,140,503 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,827
of 2,016 outputs
Outputs of similar age
#301,879
of 351,532 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#36
of 46 outputs
Altmetric has tracked 23,140,503 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,016 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 1st percentile – i.e., 1% 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 351,532 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.