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Ontology-based classification of radiological procedures for consistent sharing in Clinical Data Warehouses

Abstract : Clinical data warehouses (CDW) allow the reuse of care data in a research context. Designing and operating CDWs require addressing interoperability, data enrichment and data modeling problems, among others. This work concerns the management of medical imaging data in CDWs. It proposes a data-driven approach for classifying radiological procedures using an ontology-based approach. This approach relies on the RadLex ontology and an imaging procedures terminology called RadLex Playbook, both developed by RSNA. We first created an ontology of the radiological procedures by merging the Playbook with the relevant extract of the RadLex ontology and enriched it with French terms using the UMLS meta thesaurus. Then, we developed a proof of concept of a radiological procedures data classifier that exploits the richness of RadLex ontology and the ontological reasoning and we assessed it using medical imaging data retrieved from two different facilities. Our results demonstrate feasibility and relevance of the approach. They also highlight differences in the methods of filling imaging procedure data in the two institutions, as well as some problems in the RadLex ontology. Based on this experience, this proof of concept will be refined to evolve towards a routinely usable classification tool supporting medical imaging data management in CDWs.
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https://hal-univ-rennes1.archives-ouvertes.fr/hal-03151542
Contributor : Lotfi Senhadji <>
Submitted on : Wednesday, February 24, 2021 - 7:51:30 PM
Last modification on : Thursday, March 4, 2021 - 11:15:00 AM
Long-term archiving on: : Tuesday, May 25, 2021 - 7:03:14 PM

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  • HAL Id : hal-03151542, version 1

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Pierre Lemordant, Bernard Gibaud, Cyril Garde, Sébastien Delarche, Didier Goudet, et al.. Ontology-based classification of radiological procedures for consistent sharing in Clinical Data Warehouses. 11th International Conference on Biomedical Ontologies (ICBO), published in CEUR-WS Proceedings., Sep 2020, Bozen-Bolzano, Italy. ⟨hal-03151542⟩

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