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

Stud Health Technol Inform. 2015;216:1067.


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.

Publication types

  • Evaluation Study

MeSH terms

  • Data Mining / methods*
  • Electronic Health Records / classification*
  • Expert Systems*
  • Knowledge Bases*
  • Machine Learning
  • Natural Language Processing*
  • Pattern Recognition, Automated / methods
  • Terminology as Topic*
  • Vocabulary, Controlled