Supervised Learning for the ICD-10 Coding of French Clinical Narratives - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2020

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

Résumé

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.
Fichier principal
Vignette du fichier
MIE2020.pdf (67.02 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

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

Identifiants

  • HAL Id : hal-03020990 , version 1

Citer

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⟩
109 Consultations
331 Téléchargements

Partager

Gmail Facebook X LinkedIn More