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A Workbench for Temporal Event Information Extraction from Patient Records

  • Conference paper
Artificial Intelligence: Methodology, Systems, and Applications (AIMSA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7557))

Abstract

This paper presents a research prototype for temporal event information extraction from hospital discharge letters in Bulgarian. An algorithm for extraction of primitive events automatically sets markers for patients’ complaints, drug treatment and diagnoses with precision about 90%. Specific domain knowledge is further used to generate compound events and to identify some relations between event time sequences. Absolute and relative time information enables ordering the generated compound events using semi-intervals and fuzzy logic. Some negated events are analyzed as well to better structure the patient history.

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Author information

Authors and Affiliations

  1. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences (IICT-BAS), Sofia, Bulgaria

    Svetla Boytcheva & Galia Angelova

  2. American University in Bulgaria, Blagoevgrad, Bulgaria

    Svetla Boytcheva

Authors
  1. Svetla Boytcheva
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  2. Galia Angelova
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Editor information

Editors and Affiliations

  1. School of Computer Science, University of Manchester, Oxford Road, M13 9PL, Manchester, UK

    Allan Ramsay

  2. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, 2 Acad. G. Bonchev, 1113, Sofia, Bulgaria

    Gennady Agre

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© 2012 Springer-Verlag Berlin Heidelberg

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Boytcheva, S., Angelova, G. (2012). A Workbench for Temporal Event Information Extraction from Patient Records. In: Ramsay, A., Agre, G. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2012. Lecture Notes in Computer Science(), vol 7557. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33185-5_6

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  • DOI: https://doi.org/10.1007/978-3-642-33185-5_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33184-8

  • Online ISBN: 978-3-642-33185-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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