An Information Extraction Algorithm for Detecting Adverse Events in Neurosurgery Using Documents Written in a Natural Rich-in-Morphology Language.

Journal: Studies in health technology and informatics
Published Date: Jul 4, 2019

Abstract

Rich-in-morphology language, such as Russian, present a challenge for extraction of professional medical information. In this paper, we report on our solution to identify adverse events (complications) in neurosurgery based on natural language processing and professional medical judgment. The algorithm we proposed is easily implemented and feasible in a broad spectrum of clinical studies.

Authors

  • Gleb Danilov
    Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation.
  • Michael Shifrin
    Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation.
  • Uliya Strunina
    National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation.
  • Tatyana Pronkina
    National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation.
  • Alexander Potapov
    Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation.

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