Abstract
In this paper a psychophysical experiment and a Multidimensional Scaling (MDS) analysis are undergone to determine the physical characteristics that physicians employ to diagnose a burn depth. Subsequently, these characteristics are translated into mathematical features, correlated with these physical characteristics analysis. Finally, they are introduced to a Support Vector Machine (SVM) classifier. Results validate the ability of the mathematical features extracted from the psychophysical experiment to classify burns into their depths.
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© 2014 Springer International Publishing Switzerland
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Acha, B., Gómez-Cía, T., Fondón, I., Serrano, C. (2014). Automatic Burn Depth Estimation from Psychophysical Experiment Data. In: Roa Romero, L. (eds) XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013. IFMBE Proceedings, vol 41. Springer, Cham. https://doi.org/10.1007/978-3-319-00846-2_88
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DOI: https://doi.org/10.1007/978-3-319-00846-2_88
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-00845-5
Online ISBN: 978-3-319-00846-2
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