Supervised Learning for the ICD-10 Coding of French Clinical Narratives.

Journal: Studies in health technology and informatics
Published Date:

Abstract

Automatic detection of ICD-10 codes in clinical documents has become a necessity. In this article, after a brief reminder of the existing work, we present a corpus of French clinical narratives annotated with the ICD-10 codes. Then, we propose automatic methods based on neural network approaches for the automatic detection of the ICD-10 codes. The results show that we need 1) more examples per class given the number of classes to assign, and 2) a better word/concept vector representation of documents in order to accurately assign codes.

Authors

  • ClĂ©ment Dalloux
    Univ Rennes, Inria, CNRS, IRISA, F-35000 Rennes, France.
  • Vincent Claveau
    IRISA - CNRS, Rennes, France.
  • Marc Cuggia
    Univ Rennes, CHU Rennes, Inserm, LTSI - UMR 1099, F-35000 Rennes, France.
  • Guillaume Bouzille
    Univ Rennes, CHU Rennes, Inserm, LTSI - UMR 1099, F-35000 Rennes, France.
  • Natalia Grabar
    Université Lille 3, France.