Challenges of Ontology-Based Concept Normalization for Deep Phenotyping in Rare Skin Diseases.

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Bibliographic Details
Title: Challenges of Ontology-Based Concept Normalization for Deep Phenotyping in Rare Skin Diseases.
Authors: Bataille P; Clinical Bioinformatics Lab, Institut Imagine, INSERM UMR 1163, Université Paris Cité, Paris, France.; Department of Dermatology, Reference Center for Genodermatoses (MAGEC), Saint-Louis Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France.; Department of Paediatric Dermatology, Robert-Debré Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France., Faviez C; Clinical Bioinformatics Lab, Institut Imagine, INSERM UMR 1163, Université Paris Cité, Paris, France., Wang X; Clinical Bioinformatics Lab, Institut Imagine, INSERM UMR 1163, Université Paris Cité, Paris, France., Bannour N; Clinical Bioinformatics Lab, Institut Imagine, INSERM UMR 1163, Université Paris Cité, Paris, France., Vincent M; Clinical Bioinformatics Lab, Institut Imagine, INSERM UMR 1163, Université Paris Cité, Paris, France., Bodemer C; Department of Dermatology, Reference Center for Genodermatoses (MAGEC), Necker Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France., Garcelon N; Clinical Bioinformatics Lab, Institut Imagine, INSERM UMR 1163, Université Paris Cité, Paris, France.
Source: Studies in health technology and informatics [Stud Health Technol Inform] 2026 May 21; Vol. 336, pp. 2503-2508.
Publication Type: Journal Article
Journal Info: Publisher: IOS Press Country of Publication: Netherlands NLM ID: 9214582 Publication Model: Print Cited Medium: Internet ISSN: 1879-8365 (Electronic) Linking ISSN: 09269630 NLM ISO Abbreviation: Stud Health Technol Inform Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1879-8365
DOI:10.3233/SHTI260726