Abstract
The article presents application of artificial immune algorithms in prediction of the pO2 arterial blood gasometry parameter, which is related to the infants respiration insufficiency. Artificial immune network algorithm created for this purpose allows for time series prediction of the vectorized data sets. Training data originates from the Infant Intensive Care Unit of the Polish – American Institute of Pediatry, Collegium Medicum, Jagiellonian University in Cracow.
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Wajs, W., Swiecicki, M., Wais, P., Wojtowicz, H., Janik, P., Nowak, L. (2006). Predictive Analysis of the pO2 Blood Gasometry Parameter Related to the Infants Respiration Insufficiency. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33521-8_40
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DOI: https://doi.org/10.1007/3-540-33521-8_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33520-7
Online ISBN: 978-3-540-33521-4
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