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The Analysis of Hospital Episodes

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Book cover Medical Data Analysis (ISMDA 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2199))

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Abstract

A file of episodes stores data about the patients that are admitted to a hospital. This structure can be analyzed to obtain clinical, supervision and normative knowledge about the hospital functioning. HISYS1 is a system that integrates graphical and artificial intelligence techniques to automatically generate hospital decision support systems that organize and use the above knowledge to predict the evolution of the new patients. The system has been proved with the patients of the Hospital Joan XXIII in Tarragona (Spain) for six diagnoses.

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References

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  5. Riaño, D., Prado, S.: A Data Mining Alternative to Model Hospital Operations: Filtering, Adaptation and Behavior Prediction. In: Brause, R.W., Hanisch, E. (eds.): Medical Data Analysis. LNCS 1933. Springer-Verlag (2000) 293–299

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Author information

Authors and Affiliations

  1. Universitat Rovira i Virgili, Carretera de Salou s/n, 43006, Tarragona, Spain

    David Riaño

  2. Informàtica El Corte Inglés, Bolivia 234, 08020, Barcelona, Spain

    Susana Prado

Authors
  1. David Riaño
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  2. Susana Prado
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Editor information

Editors and Affiliations

  1. Polytechnical University of Madrid Artificial Intelligence Laboratory, Medical Informatics Group, 28660, Boadilla del Monte (Madrid), Spain

    Jose Crespo  & Victor Maojo  & 

  2. Health Bioinformatics Unit, Institute of Health Carlos III, Ctra. de Majadahonda-Pozuelo Km.2, 28220, Majadahonda (Madrid), Spain

    Fernando Martin

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© 2001 Springer-Verlag Berlin Heidelberg

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Riaño, D., Prado, S. (2001). The Analysis of Hospital Episodes. In: Crespo, J., Maojo, V., Martin, F. (eds) Medical Data Analysis. ISMDA 2001. Lecture Notes in Computer Science, vol 2199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45497-7_35

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  • DOI: https://doi.org/10.1007/3-540-45497-7_35

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42734-6

  • Online ISBN: 978-3-540-45497-7

  • eBook Packages: Springer Book Archive

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