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Transformer-based structuring of Italian electronic health records with application in cardiac settings
2026-01-23
health informatics
Title + abstract only
View on medRxiv
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PurposeNatural Language Processing (NLP) has the potential to extract structured clinical knowledge from unstructured Electronic Health Records (EHRs). However, the limited availability of annotated datasets for algorithm training restricts its application in clinical practice. This study investigates the use of transformer-based NLP models to structure Italian EHRs in cardiac settings, addressing this gap. MethodsWe implemented and evaluated three named entity recognition algorithms: SpaCy, Fl...
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