Factors influencing specificity and sensitivity of injury severity prediction (ISP) algorithm for AACN

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Abstract

To improve the accuracy of Injury Severity Prediction in the event of vehicle crash, a new methodology is proposed using the US vehicle accident database (NASS-CDS). This proposed method is an extension of the base algorithm introduced by Kononen et al. in which, some of the additional variables were introduced and branched logistic regression methodology was used. Results suggest that the proposed branching method has some advantage over the base algorithm due to better linearization of the complex multidimensional non-linear relationship of the input and output variables.

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Pal, C., Okabe, T., Kulothungan, V., Sangolla, N., Manoharan, J., Stewart, W., & Combest, J. (2016). Factors influencing specificity and sensitivity of injury severity prediction (ISP) algorithm for AACN. International Journal of Automotive Engineering, 7(1), 15–22. https://doi.org/10.20485/jsaeijae.7.1_15

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