Data harmonization and federated learning for multi-cohort dementia research using the OMOP common data model: A Netherlands consortium of dementia cohorts case study

Background: Establishing collaborations between cohort studies has been fundamental for progress in health research. However, such collaborations are hampered by heterogeneous data representations across cohorts and legal constraints to data sharing. The first arises from a lack of consensus in standards of data collection and representation across cohort studies and is usually tackled by applying data harmonization processes. The second is increasingly important due to raised awareness for privacy protection and stricter regulations, such as the GDPR. Federated learning has emerged as a priva... Mehr ...

Verfasser: Mateus, Pedro
Moonen, Justine
Beran, Magdalena
Jaarsma, Eva
van der Landen, Sophie M.
Heuvelink, Joost
Birhanu, Mahlet
Harms, Alexander G.J.
Bron, Esther
Wolters, Frank J.
Cats, Davy
Mei, Hailiang
Oomens, Julie
Jansen, Willemijn
Schram, Miranda T.
Dekker, Andre
Bermejo, Inigo
Dokumenttyp: Artikel
Erscheinungsdatum: 2024
Schlagwörter: CDM / Cohort studies / Data harmonization / ETL / Federated learning / OMOP / Health Informatics / Computer Science Applications
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-29203975
Datenquelle: BASE; Originalkatalog
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Link(s) : https://dspace.library.uu.nl/handle/1874/454166