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Evaluation of a hospital admission prediction model adding coded chief complaint data using neural network methodology

Overview of attention for article published in European Journal of Emergency Medicine: Official Journal of the European Society for Emergency Medicine, April 2015
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Article details
Title
Evaluation of a hospital admission prediction model adding coded chief complaint data using neural network methodology
Published in
European Journal of Emergency Medicine: Official Journal of the European Society for Emergency Medicine, April 2015
DOI 10.1097/mej.0000000000000126
Pubmed ID
Authors
Abstract

Our objective was to apply neural network methodology to determine whether adding coded chief complaint (CCC) data to triage information would result in an improved hospital admission prediction model than one without CCC data.

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X Demographics

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 8 20%
Student > Ph. D. Student 7 17%
Researcher 5 12%
Student > Doctoral Student 2 5%
Student > Bachelor 2 5%
Other 3 7%
Unknown 14 34%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 10 24%
Computer Science 5 12%
Engineering 4 10%
Nursing and Health Professions 3 7%
Environmental Science 1 2%
Other 2 5%
Unknown 16 39%
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 13 March 2015.
All research outputs
#28,597,744
of 34,357,314 outputs
Outputs from European Journal of Emergency Medicine: Official Journal of the European Society for Emergency Medicine
#1,204
of 1,583 outputs
Outputs of similar age
#241,591
of 307,417 outputs
Outputs of similar age from European Journal of Emergency Medicine: Official Journal of the European Society for Emergency Medicine
#21
of 21 outputs
Altmetric has tracked 34,357,314 research outputs across all sources so far. This one is in the 9th percentile – i.e., 9% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,583 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 2nd percentile – i.e., 2% 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 307,417 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 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.