Annotation methods to develop and evaluate an expert system based on natural language processing in electronic medical records.

Journal: Studies in health technology and informatics
Published Date:

Abstract

The objective of the SYNODOS collaborative project was to develop a generic IT solution, combining a medical terminology server, a semantic analyser and a knowledge base. The goal of the project was to generate meaningful epidemiological data for various medical domains from the textual content of French medical records. In the context of this project, we built a care pathway oriented conceptual model and corresponding annotation method to develop and evaluate an expert system's knowledge base. The annotation method is based on a semi-automatic process, using a software application (MedIndex). This application exchanges with a cross-lingual multi-termino-ontology portal. The annotator selects the most appropriate medical code proposed for the medical concept in question by the multi-termino-ontology portal and temporally labels the medical concept according to the course of the medical event. This choice of conceptual model and annotation method aims to create a generic database of facts for the secondary use of electronic health records data.

Authors

  • Quentin Gicquel
    Université Lyon 1, UMR CNRS UCBL 5558, Lyon, France.
  • Nastassia Tvardik
    Université Lyon 1, UMR CNRS UCBL 5558, Lyon, France.
  • Côme Bouvry
    Université Lyon 1, UMR CNRS UCBL 5558, Lyon, France.
  • Ivan Kergourlay
    Department of Biomedical Informatics, Rouen University Hospital, TIBS, LITIS EA 4108 Rouen University, France.
  • André Bittar
    Holmes Semantic Solutions, Grenoble, France.
  • Frédérique Segond
    Viseo Technologies, Grenoble, France.
  • Stefan Darmoni
    Department of Biomedical Informatics, Rouen University Hospital, TIBS, LITIS EA 4108 Rouen University, France.
  • Marie-Hélène Metzger
    Université Lyon 1, UMR CNRS UCBL 5558, Lyon, France.