Evaluation of clinical named entity recognition methods for Serbian electronic health records.

Journal: International journal of medical informatics
PMID: 35653828

Abstract

BACKGROUND AND OBJECTIVES: The importance of clinical natural language processing (NLP) has increased with the adoption of electronic health records (EHRs). One of the critical tasks in clinical NLP is named entity recognition (NER). Clinical NER in the Serbian language is a severely under-researched area. The few approaches that have been proposed so far are based on rules or machine-learning models with hand-crafted features, while current state-of-the-art models have not been explored. The objective of this paper is to assess the performance of state-of-the-art NER methods on clinical narratives in the Serbian language.

Authors

  • Aleksandar Kaplar
    Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia.
  • Milan Stošović
    Clinic of Nephrology, University Clinical Center of Serbia, Belgrade, Serbia.
  • Aleksandra Kaplar
    Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia.
  • Voin Brković
    Clinic of Nephrology, University Clinical Center of Serbia, Belgrade, Serbia.
  • Radomir Naumović
    Clinic of Nephrology, University Clinical Center of Serbia, Belgrade, Serbia.
  • Aleksandar Kovacevic
    Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia.

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