Semi-Automated Approach to Retrieve SNOMED CT Hierarchy of Clinical Terms by Using Terminology Server.

KNIME RESTful API Methods SNOMED CT Semantic Interoperability Snowstorm Terminology Server

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:
02 May 2023
Historique:
medline: 15 5 2023
pubmed: 12 5 2023
entrez: 12 5 2023
Statut: ppublish

Résumé

SNOMED CT has an enormous number of clinical concepts and mapping to SNOMED CT is considered as the foundation to achieve semantic interoperability in healthcare. Manual mapping is time-consuming and error-prone thus making this crucial step challenging. In addition, hierarchy retrieval of clinical concepts increases the challenges for the user. Terminology Servers provide an interface, which can be used to automate the process of retrieving data. In this work, it is shown that Snowstorm can significantly improve the efficiency of retrieval process if used with semi-automated workflows.

Identifiants

pubmed: 37172170
pii: SHTI230029
doi: 10.3233/SHTI230029
doi:

Types de publication

Journal Article

Langues

eng

Pagination

142-147

Auteurs

Abdul Mateen Rajput (AM)

Medical Directorate, Medizincontrolling, Inselspital, University Hospital Bern, Insel Gruppe, Bern, Switzerland.

Karen Triep (K)

Medical Directorate, Medizincontrolling, Inselspital, University Hospital Bern, Insel Gruppe, Bern, Switzerland.

Olga Endrich (O)

Medical Directorate, Medizincontrolling, Inselspital, University Hospital Bern, Insel Gruppe, Bern, Switzerland.

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Classifications MeSH