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Integration and Harmonization of Multi-Source Obstetric Data Using Rule-Based NLP for Fetomaternal Risk Modelling.

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Title: Integration and Harmonization of Multi-Source Obstetric Data Using Rule-Based NLP for Fetomaternal Risk Modelling.
Authors: Barrenetxea J; Institute of Medical Informatics, Charité-Universitätsmedizin Berlin, Berlin, Germany., Grünewald E; Institute of Medical Informatics, Charité-Universitätsmedizin Berlin, Berlin, Germany., Tabernig B; Department of Obstetrics, Charité-Universitätsmedizin Berlin, Berlin, Germany., Sommer J; Department of Obstetrics, Charité-Universitätsmedizin Berlin, Berlin, Germany., Schmiedler R; Institute of Medical Informatics, Charité-Universitätsmedizin Berlin, Berlin, Germany., Sommer L; Institute of Medical Informatics, Charité-Universitätsmedizin Berlin, Berlin, Germany., Sonnabend I; Department of Obstetrics, Charité-Universitätsmedizin Berlin, Berlin, Germany., Ernst C; Department of Obstetrics and Prenatal Medicine, University Hospital Bonn, Bonn, Germany., Recker F; Department of Obstetrics and Prenatal Medicine, University Hospital Bonn, Bonn, Germany., Wegener S; Department of Obstetrics, Charité-Universitätsmedizin Berlin, Berlin, Germany., Balzer F; Institute of Medical Informatics, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Source: Studies in health technology and informatics [Stud Health Technol Inform] 2026 May 21; Vol. 336, pp. 1575-1576.
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
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