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An artificial neural network to safely reduce the number of ambulance ECGs transmitted for physician assessment in a system with prehospital detection of ST elevation myocardial infarction

Overview of attention for article published in Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, February 2012
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1 X user
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1 Facebook page

Citations

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14 Dimensions

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61 Mendeley
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Title
An artificial neural network to safely reduce the number of ambulance ECGs transmitted for physician assessment in a system with prehospital detection of ST elevation myocardial infarction
Published in
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, February 2012
DOI 10.1186/1757-7241-20-8
Pubmed ID
Authors

Jakob L Forberg, Ardavan Khoshnood, Michael Green, Mattias Ohlsson, Jonas Björk, Stefan Jovinge, Lars Edenbrandt, Ulf Ekelund

Abstract

Pre-hospital electrocardiogram (ECG) transmission to an expert for interpretation and triage reduces time to acute percutaneous coronary intervention (PCI) in patients with ST elevation Myocardial Infarction (STEMI). In order to detect all STEMI patients, the ECG should be transmitted in all cases of suspected acute cardiac ischemia. The aim of this study was to examine the ability of an artificial neural network (ANN) to safely reduce the number of ECGs transmitted by identifying patients without STEMI and patients not needing acute PCI.

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 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Sweden 1 2%
Canada 1 2%
Unknown 58 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 16%
Student > Ph. D. Student 6 10%
Student > Master 6 10%
Student > Bachelor 6 10%
Professor 5 8%
Other 15 25%
Unknown 13 21%
Readers by discipline Count As %
Medicine and Dentistry 22 36%
Engineering 7 11%
Nursing and Health Professions 7 11%
Agricultural and Biological Sciences 2 3%
Unspecified 2 3%
Other 5 8%
Unknown 16 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 22 February 2012.
All research outputs
#16,721,208
of 25,373,627 outputs
Outputs from Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine
#1,063
of 1,365 outputs
Outputs of similar age
#169,130
of 253,530 outputs
Outputs of similar age from Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine
#12
of 16 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,365 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 18th percentile – i.e., 18% 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 253,530 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.