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Bo Vanhoof edited this page 2026-02-02 16:28:12 +01:00

Welcome to the NLP>OMOP Wiki.

The main objectives of the NLP > OMOP project are as follows:

1. Transform unstructured medical data into structured formats by applying Natural Language Processing (NLP) techniques and mapping the results to the OMOP Common Data Model using Snomed CT terminology.
2. Enable semantic interoperability across participating hospitals by standardising clinical concepts and data structures.
3. Facilitate secondary use of health data for research, innovation, and policy-making through structured and anonymised datasets.
4. Demonstrate technical and clinical feasibility of integrating NLP-derived data into OMOP databases within operational hospital environments.
5. Establish a scalable and reusable framework that can be extended to other hospitals and used in all clinical domains.
6. Ensure compliance with data protection regulations and implement robust governance for secure data processing and sharing.

The project was coordinated by Bram De Caluwé (bram.de.caluwe@klina.be)