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A neural network approach for symbolic interpretation in critical care

  • Methodology for Data Analysis, Task Selection and Nets Design
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Biological and Artificial Computation: From Neuroscience to Technology (IWANN 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1240))

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Abstract

In this paper, the authors present a work-in-process neural model trained to symbolically characterize the numeric parameters of critical patients in Intensive Care Units (ICUs). The nets were designed to assign the state {very high, high, normal, low, very low} of the main haemodinamic and respiratory parameters based on the particular context of the patient. This symbolic processing allows the use of an heuristic, general module, which prescribes ventilation and oxygenation therapies and shows the diagnoses corresponding to the symbolic labels of those variables.

The problems derived from the neural features of the proposed model are commented, holding the collection of a large patient database by using a Clinical Information System (Carevue 9000), the definition of the persistence/validity of asynchronous values — half life of drugs, lab results — and temporal evolution of trends.

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Authors and Affiliations

  1. Laboratorio de Investigation y Desarrollo en lnteligencia Artificial (LIDIA) Department of Computer Science, University of La Coruña, E15071, Coruña, Spain

    Vicente Moret-Bonillo, Jorge Díaz Fernández & Elena Hernández Pereira

Authors
  1. Vicente Moret-Bonillo
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  2. Jorge Díaz Fernández
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  3. Elena Hernández Pereira
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Editor information

José Mira Roberto Moreno-Díaz Joan Cabestany

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© 1997 Springer-Verlag Berlin Heidelberg

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Moret-Bonillo, V., Fernández, J.D., Pereira, E.H. (1997). A neural network approach for symbolic interpretation in critical care. In: Mira, J., Moreno-Díaz, R., Cabestany, J. (eds) Biological and Artificial Computation: From Neuroscience to Technology. IWANN 1997. Lecture Notes in Computer Science, vol 1240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0032555

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  • DOI: https://doi.org/10.1007/BFb0032555

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63047-0

  • Online ISBN: 978-3-540-69074-0

  • eBook Packages: Springer Book Archive

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