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Eur J Trauma Emerg Surg (2017) 43:805–822 DOI 10.1007/s00068-016-0757-3 ORIGINAL ARTICLE Survival prediction of trauma patients: a study on US National Trauma Data Bank 1 2 3 4 5 I. Sefrioui · R. Amadini · J. Mauro · A. El Fallahi · M. Gabbrielli Received: 22 July 2016 / Accepted: 29 December 2016 / Published online: 22 February 2017 © Springer-Verlag Berlin Heidelberg 2017 Abstract Methods In this work we evaluate different approaches Background Exceptional circumstances like major inci- for predicting whether a patient will survive or not accord- dents or natural disasters may cause a huge number of ing to simple and easily measurable observations. We con- victims that might not be immediately and simultaneously ducted a rigorous, comparative study based on the most saved. In these cases it is important to define priorities important prediction techniques using real clinical data of avoiding to waste time and resources for not savable vic- the US National Trauma Data Bank. tims. Trauma and Injury Severity Score (TRISS) methodol- Results Empirical results show that well-known Machine ogy is the well-known and standard system usually used by Learning classifiers can outperform the TRISS meth- practitioners to predict the survival probability of trauma odology. Based on our findings, we can say
European Journal of Trauma and Emergency Surgery – Springer Journals
Published: Feb 22, 2017
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