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Automatic Classification for Decision Making of the Severeness of the Acute Radiation Syndrome

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Part of the book series: Advances in Soft Computing ((AINSC,volume 46))

Summary

Decision making of the severeness of the acute radiation syndrome is a major challenge due to the fact that the radiation dose is not known and cannot easily be reconstructed. Although radiation accidents are relatively rare, an automatic damage classification for individual medical prognosis of the health status of a patient is necessary. Under the threat of nuclear terroristic attacks the problem has received special attention.

Early classification of the severeness of the damage in case of the acute radiation syndrome allows for separation of patients with irreversibly damaged cell renewal systems from those with reversible damage. As a consequence, the available resources for the treatment of patients can be used most efficiently and, especially, therapeutic actions for patients with irreversible cell damage can be taken in time.

This paper concentrates on the damage to the hemopoietic system. Measurements from available patient data are represented by time series of cell counts of the relevant blood cell lines. Features extracted from reduced dynamic models form the basis for automatic damage classification where emphasis is on an early classification based on a time horizon not exceeding 10 days. Our newest results guarantee a generalization rate in the range of 80%.

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Van-Nam Huynh Yoshiteru Nakamori Hiroakira Ono Jonathan Lawry Vkladik Kreinovich Hung T. Nguyen

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© 2008 Springer-Verlag Berlin Heidelberg

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Mehr, K., Hofer, E.P. (2008). Automatic Classification for Decision Making of the Severeness of the Acute Radiation Syndrome. In: Huynh, VN., Nakamori, Y., Ono, H., Lawry, J., Kreinovich, V., Nguyen, H.T. (eds) Interval / Probabilistic Uncertainty and Non-Classical Logics. Advances in Soft Computing, vol 46. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77664-2_28

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  • DOI: https://doi.org/10.1007/978-3-540-77664-2_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77663-5

  • Online ISBN: 978-3-540-77664-2

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