Supervised Learning for the ICD-10 Coding of French Clinical Narratives - Inria - Institut national de recherche en sciences et technologies du numérique
Conference Papers Year : 2020

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

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.
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Dates and versions

hal-03020990 , version 1 (24-11-2020)

Identifiers

  • HAL Id : hal-03020990 , version 1

Cite

Clément Dalloux, Vincent Claveau, Marc Cuggia, Guillaume Bouzillé, Natalia Grabar. Supervised Learning for the ICD-10 Coding of French Clinical Narratives. MIE 2020 - Medical Informatics Europe conference - Digital Personalized Health and Medicine, Apr 2020, Geneva, Switzerland. pp.1-5. ⟨hal-03020990⟩
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