Using Equivalent Classes of an Ontology to Understand Care Pathway in Amyotrophic Lateral Sclerosis.


Journal

Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582

Informations de publication

Date de publication:
04 Jul 2019
Historique:
entrez: 27 7 2019
pubmed: 28 7 2019
medline: 3 9 2019
Statut: ppublish

Résumé

To understand the home-based difficulties encountered in the health care pathways of patients with Amyotrophic Lateral Sclerosis (ALS), we must annotate a large amount of textual data, from a database created by the ALS Île de France coordination network. For this purpose, we have developed a modular ontology, consisting of four modules, and a semantic annotation tool integrating the created ontology. The specificity of our approach is the creation of equivalent classes at different levels of the ontology. These equivalent classes represent variables of interest allowing a statistical approach and a clinical analysis of comprehension of care pathways ruptures causing.

Identifiants

pubmed: 31349274
pii: SHTI190025
doi: 10.3233/SHTI190025
doi:

Types de publication

Journal Article

Langues

eng

Pagination

93-96

Auteurs

Sonia Cardoso (S)

Institut du Cerveau et de la Moelle épinière, ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France.
Sorbonne Université, INSERM, Univ. Paris 13, LIMICS, Paris, France.

Xavier Aimé (X)

Sorbonne Université, INSERM, Univ. Paris 13, LIMICS, Paris, France.

Vincent Meininger (V)

Ramsay General de Santé, Hôpital Peupliers Paris, France.

David Grabli (D)

AP-HP Pitié Salpêtrière, Dépt des maladies du Système Nerveux, Paris, France.

Pierre Meneton (P)

Sorbonne Université, INSERM, Univ. Paris 13, LIMICS, Paris, France.

Jean Charlet (J)

Sorbonne Université, INSERM, Univ. Paris 13, LIMICS, Paris, France.
Assistance Publique-Hôpitaux de Paris, DRCI, Paris, France.

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Classifications MeSH