Ensembled neural networks applied to modeling survival rate for the patients with out-of-hospital cardiac arrest View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2012-12

AUTHORS

Yuan-Jang Jiang, Matthew Huei-Ming Ma, Wei-Zen Sun, Kuan-Wu Chang, Maysam F. Abbod, Jiann-Shing Shieh

ABSTRACT

The purpose of this study is to use ensembled neural networks (ENN) to model survival rate for the patients with out-of-hospital cardiac arrest (OHCA). We also use seven different sensitivity analyses to find out the important variables to establish a comprehensive and objective assessment method for the OHCA patients. After pre-filtering, we obtained 4,095 data for building this ENN model. The data have been divided into 60 % data for training, 20 % data for validation, and 20 % data for testing. The 11 inputs, including response time, on-scene time, patient transfer time, time to cardiopulmonary resuscitation (CPR), CPR on the scene, using drugs, age, gender, using airway, using automated external defibrillator (AED), and trauma type, and one output variable have been selected as ENN model structure. The results have been shown that ENN can model the OHCA patients and CPR on the scene, using drugs, on-scene time, and using airway in the top 4 of these 11 important variables after 7 different sensitivity analyses. Moreover, these four variables have also been shown significant differences when we use traditional one variable statistics analysis for these variables. More... »

PAGES

241-244

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10015-012-0048-y

DOI

http://dx.doi.org/10.1007/s10015-012-0048-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1019259549


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141 Department of Mechanical Engineering, Yuan Ze University, 135 Yuan-Tung Rd, 320, Chung-Li, Taoyuan, Taiwan
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143 https://www.grid.ac/institutes/grid.413050.3 schema:alternateName Yuan Ze University
144 schema:name Department of Mechanical Engineering, Yuan Ze University, 135 Yuan-Tung Rd, 320, Chung-Li, Taoyuan, Taiwan
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146 https://www.grid.ac/institutes/grid.7728.a schema:alternateName Brunel University London
147 schema:name School of Engineering and Design, Brunel University, London, UK
148 rdf:type schema:Organization
 




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