Neural networks for prediction of trauma victim's outcome. Comparison with the TRISS and Revised Trauma Score

Theodoraki, E-M; Koukouvinos, C; Parpoula, C

dc.contributor.author	Theodoraki, E-M	en
dc.contributor.author	Koukouvinos, C	en
dc.contributor.author	Parpoula, C	en
dc.date.accessioned	2014-03-01T02:46:53Z
dc.date.available	2014-03-01T02:46:53Z
dc.date.issued	2010	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32919
dc.subject	Area Under The Curve	en
dc.subject	Logistic Regression	en
dc.subject	Prediction Model	en
dc.subject	Neural Network	en
dc.subject	Neural Network Model	en
dc.subject	Revised Trauma Score	en
dc.subject.other	Area under the curves	en
dc.subject.other	Input variables	en
dc.subject.other	Logistic regressions	en
dc.subject.other	Neural network model	en
dc.subject.other	Predictive models	en
dc.subject.other	Probability of survival	en
dc.subject.other	Information technology	en
dc.subject.other	Neural networks	en
dc.title	Neural networks for prediction of trauma victim's outcome. Comparison with the TRISS and Revised Trauma Score	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ITAB.2010.5687802	en
heal.identifier.secondary	5687802	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ITAB.2010.5687802	en
heal.publicationDate	2010	en
heal.abstract	Last decades predictive models that assess probability of survival for trauma victims have been developed. Some of the most commonly used are the TRISS methodology, the logistic regression modelling technique, and the Revised Trauma Score which derive from specific input variables. However recently, the development of neural network models reveal encouraging results as they most of the times outperform the traditional approaches. In this paper we present models' predictability comparing the Area Under the Curve and we discuss the results. © 2010 IEEE.	en
heal.journalName	Proceedings of the IEEE/EMBS Region 8 International Conference on Information Technology Applications in Biomedicine, ITAB	en
dc.identifier.doi	10.1109/ITAB.2010.5687802	en